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With the development of industrial demand, precise identification of system models is currently required in the field of industrial control, which limits the whale search algorithm. In response to the fact that whale optimization algorithms are prone to falling into local optima and the identification of important Hammerstein models ignores the issue of noise outliers in actual industrial environments, this study improves the whale algorithm and constructs a Hammerstein model identification strategy for nonlinear systems under heavy-tailed noise using the improved whale algorithm. Results showed that it had a lower rank average and an average success rate of 95.65%. It found the global optimum when the number of iterations reached around 150 and had faster convergence speed and accuracy. In identifying Hammerstein model under heavy-tailed noise, the average prediction recognition accuracy of the improved whale algorithm was 92.38%, the determination coefficient was 0.89, the percentage fitting error was 0.03, and the system error was 0.02. This research achievement has certain value in the field of industrial control and can serve as a technical reference. [ABSTRACT FROM AUTHOR]

In recent years, with the development of 'China's new urbanization, the "characteristic town movement" with the development of industrial economy first has brought problems to a large number of rural settlements, such as no cultural planning, no consumption of industry, and no soul. Then, in reality, there are still a large number of rural settlements under the planning of the upper-level local government, with the goal of developing into a characteristic town in the future. Therefore, this study believes that there is an urgent need to build a framework for evaluating the construction potential of rural settlements with sustainable characteristic towns. Not only that but also a decision analysis model should be provided for real-world empirical cases. This model needs to cover the assessment of the sustainable development potential of characteristic towns as the goal and the formulation of improvement strategies. This study combines the data collection of current characteristic town development rating reports, applies data exploration technology to extract core impact elements and obtain hierarchical decision rules, integrates expert domain knowledge with DEMATEL technology, and establishes an impact network relationship diagram between core impact elements. At the same time, the representative characteristic town cases are assessed for their sustainable development potential, and the modified VIKOR technique is applied to clarify the actual problems of the empirical cases, in an attempt to determine whether the development potential and development plan of the characteristic town meet the sustainable development needs from the pre-evaluation mechanism. [ABSTRACT FROM AUTHOR]

The double-layer charge can effectively improve the axial driving ability of explosives, which shows a considerable engineering application prospect in highly efficient damage warheads. Due to the complex wave structure produced by the overpressure detonation of a double-layer charge, a series of dynamic behaviors inside the shaped charge liner will be affected. By comparing the detonation wave shapes of single-layer charge and double-layer shaped charge structure and the jet shaping parameters of a double-layer shaped charge with different structural parameters, the evolution of detonation wave and the state parameters in the wave system are analyzed in this research. The research found that the double-layer charge with high detonation velocity in the outer layer and low detonation velocity in the inner layer can produce continuous overpressure detonation, which makes the overpressure detonation state be applied efficiently. Meanwhile, this study found that the overpressure detonation field formed by the double-layer charge changes the action law of the traditional single charge on the shaped charge liner. The detonation waveform of the entire charge is controlled by different detonation velocities and detonation energies, and a detonation waveform that matched well with the shaped charge liner is obtained. This study solves the matching relationship between the structure of the overpressure detonation wave system and the properties of a double-layer charge, which is of great value for improving the detonation-driving effect of condensed explosives on surrounding media. The double-layer charge can effectively enhance the potential of explosive charge. It is not only widely used in military fields such as improving the armor-breaking power of shaped charge penetrators and improving the muzzle velocity and concentration of fragments of directional warheads, but also can promote the development of industrial fields such as explosive processing. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the influence of high hydrostatic pressure (HHP) pretreatment (200 MPa (HHP1) and 400 MPa (HHP 2)) on the drying of plum slices and on the physical, morphostructural and total phenolic compounds of its dust. Drying was carried out at a temperature of 70°C and an air velocity of 2.0 m s−1. The application of 400 MPa (HHP2) promoted a 34% reduction in drying time (210 min), higher drying rate, and variation in effective diffusivity from 6.703 to 14.273 × 10−4 m2 min−1 between the terms of the Check The GAB model was more suitable to determine the equilibrium moisture content (R2 > 0.99 and p < 10%). The plum powders showed a water activity lower than 0.22 (p ≥.05), the increase in HHP promoted an increase in the water solubility index and total phenolic compounds. Larger irregularities such as pores and cavities were observed on the powder surface for HHP2 and the spectra indicated that the intensities of the characteristic bands were significantly altered with the application of HHP. Therefore, the results of this study provide information for the potential application of HHP as a drying pretreatment. Practical applications: High hydrostatic pressure (HHP) as a pretreatment for convective drying of plums is a promising technology. This study was based on pretreatment with HHP, for which we investigated changes in drying parameters, physical, and morphostructural properties of the powder. Through this study, we hope to provide a theoretical basis for the application of HHP with pre‐drying treatment and consequently industrial development of plum powder. [ABSTRACT FROM AUTHOR]

In the post-epidemic era, it is difficult for farmers to sell agricultural products offline due to their characteristics, and farmers once again fall into the situation of "difficult sales." New media marketing of agricultural products, as an emerging form conforming to the trend of the times, not only increases farmers' income but also promotes industrial integration and development. However, as this model is still in the early stage of development, a large number of farmers are not willing to transform the traditional sales channels into new media marketing for agricultural product sales. In this study, the interview data of 76 new-type professional farmers in Fujian were analyzed by three-level coding based on programmed grounded theory. It is found that core factors, and macro- and microfactors such as farmers' characteristics and sales situation will affect farmers' willingness to sell agricultural products through new media. Therefore, this study deeply explores the relationship between farmers' willingness and various factors and puts forward three suggestions for solving the actual problems of agricultural product sales. [ABSTRACT FROM AUTHOR]

The country is developing rapidly and the economy is taking off. For the country, the economic development of each region is very important, and the economy is the key to measuring the development of a region. To this end, the machine learning model is combined with regional economic scale prediction and management, and the two are studied together to obtain the following: (1) The key to measuring the regional economy is the growth rate of GDP and GDP. For the economic comparison between region A and region B, the economic scale is predicted by machine learning model. The regional economic development is better, which has an important basis for the comparison of the following methods. (2) There are many ways to improve the regional economy. Among them, the development of the industrial economy has the highest degree of regional economic indicators GDP and GDP growth rate. (3) The machine learning model has many benefits in the development of regional economic forecasting. Among them, reducing errors has the greatest impact on the regional economy. By comparison, it can be known that the accuracy of the regional economic forecasting under the machine learning model and the required forecasting time have been greatly optimized. [ABSTRACT FROM AUTHOR]

In order to maintain the sustainable development of resource-based industrial clusters, research on the coupling relationship between resource-based industrial clusters and regional innovation networks is proposed. Combined with the historical data of 11 typical resource-based cities from 2013 to 2021, the grey relational model is used to measure the correlation between resource-based clusters and regional innovation networks. And the concept of capacity coupling and the capacity coupling coefficient model in physics is used as a reference to obtain the coupling degree model of resource-based industrial clusters and regional innovation networks. The coupling degree model is used to measure the coupling degree of the two, and a reasonable analysis is carried out on the result of the measurement. The results show that there is a correlation between resource-based industrial clusters and regional innovation networks. And the correlation between the two is above 0.65, indicating a strong correlation. The coupling between resource-based industrial clusters and regional innovation networks has entered the subsequent high-level coupling stage from the run-in coupling stage that began in 2013 and continues to maintain a high-level coupling. It is pointed out that cluster governance plans should be formulated according to regional differences and local conditions, so as to guide the transformation and upgrading of resource-based industrial clusters and to avoid the negative impact on the regional economy due to resource exhaustion. [ABSTRACT FROM AUTHOR]

With the rapid modernization of China's economic development, especially urbanization, China's rural economy is clearly lagging behind the overall development level of the Chinese economy, with low industrial efficiency, irrational industrial structure, and unbalanced industrial development. The development of rural tourism brings new opportunities for industrial integration and industrial transformation and upgrading in rural China. This study draws on a case study of Zhonghaoyu village in Shandong province, China, to summarize the important experience of the transformation and upgrading of the industrial structure of Chinese tourism villages by observing and analysing the changes in the industrial structure of Zhonghaoyu village before and during the development of rural tourism. Prior to the development of rural tourism, Zhonghaoyu Village was a mountainous village that relied almost entirely on farming. Through years of rural tourism development, the service industry in Zhonghoayu Village has grown, reflecting the driving effect of rural tourism, but the service industry is small and agriculture still dominates, and its role and position in the overall economic development of the village has not been highlighted. As the transformation of the shareholding system of rural tourism in Zhonghaoyu Village was completed, the original decentralized operation of farmers was replaced by corporate operation, and the service industry led by tourism was developed comprehensively and rapidly, and the development of rural tourism promoted the completion of the transformation and upgrading of the industrial structure of Zhonghaoyu Village. [ABSTRACT FROM AUTHOR]

With the strong development of industrial transformation, the digital economy, as the most dynamic, innovative, and widely radiated economic form at present, has become an important force driving the development of the global economy. Shaanxi Province has accelerated the development of the digital economy, and the development of the province's digital economy has shown a good trend. However, the current digital economy development measurement is still unable to accurately observe the development law of the digital economy industry, which makes it difficult to measure the control standards for the digital economy industry. Therefore, this study has evaluated the development of digital economy in Shaanxi Province based on machine learning algorithms. This study first puts forward the dimensions of digital economy monitoring and evaluation and then combines the characteristics of digital economy development in Shaanxi Province to determine the quality evaluation indicators of digital economy development. Finally, according to the machine learning algorithm, a quality evaluation model of digital economy development was established, and through the evaluation results, suggestions were put forward for the development plan of digital economy in Shaanxi Province. The experimental results showed that, after re-planning the digital economy in Shaanxi Province according to the evaluation results, the development of the digital economy in Shaanxi Province has increased by 9.82%, indicating that the evaluation model plays a good reference role in the formulation of the digital economy development plan. [ABSTRACT FROM AUTHOR]

The traditional impact analysis method for the economic development of marine industries does not consider the impact weight of different marine industries, which leads to an unsatisfactory effect on sustainable development after the optimized management of resources. Therefore, a new method is designed to solve the above problems; by analyzing the scale, hierarchical system, and optimizing the spatial resource framework of the marine industry, the influence of different marine industries is comprehensively measured, and the final demand dependency of the marine industry economy is obtained. The comprehensive index system is designed to evaluate the economic development of the marine industry, and the linear weighted sum method is used to calculate the sustainable development degree of marine industry economy in different regions. The results show that the final evaluation score of the marine biological industry in Shandong Province is 64.97, which is affected by comprehensive factors. The scores of capital and environmental governance are between 84.03 and 82.87, respectively, which are the main factors to achieve sustainable development. After the optimization of this method, the demand dependence of relevant regions is reduced, and the sustainable development level is effectively improved, indicating that the sustainable state of this method is better. The resource optimization path given by the research can be further applied to the construction process of marine and industrial economic development in other provinces and cities so as to comprehensively improve the quality and effect of marine economic growth. [ABSTRACT FROM AUTHOR]

Mining and utilizing cultural heritage resources and creating and developing creative and cultural industries have become the priority direction of economic development, setting off a wave of cultural heritage resource development, and industrial transformation. Which cultural heritage resources can have the high value of industrial transformation has become one of the research topics that have attracted much attention. In view of this problem, research is of great significance to the development of cultural heritage resources and the field of industrial transformation. With the in-depth research on resource development and industrial transformation, the research on artificial neural network (ANN) in cultural industry transformation is gradually carried out, and its performance advantages are of great significance to solve the problem of value evaluation. This paper aims to study the application of the value assessment method based on the BP neural network (BPNN) in the development of cultural heritage resources and industrial transformation. Through the analysis and research of BPNN and cultural heritage resource development and industrial transformation, it can be applied to the construction of resource value assessment methods to solve the problem of improving the value level of cultural heritage resource development and industry. This paper analyzes BPNN, cultural heritage, and value evaluation methods, conducts experimental analysis on the performance of the algorithm, and uses related theoretical formulas to explain. The results show that the evaluation method has passed the random consistency test, and the results are valid. The obtained index popularity weight value is 0.134, the economic benefit weight value is 0.093, and the resource correlation degree weight value is 0.074, which can be used as the key criteria for resource value evaluation. The classification of resources through resource value assessment can provide theoretical support for the development and industrialization of cultural heritage and can meet the needs of improving the value and quality of cultural heritage development and industrial transformation, and the development level and satisfaction have been greatly improved. [ABSTRACT FROM AUTHOR]

Intangible cultural heritage is very important for the development of a nation. There are clear instructions for the history and inheritance of a country. Tao represents the inheritance of a country in time, and the sustainable development of the protection and inheritance of intangible cultural heritage and derivative cultural products is of great significance. From the past to the present, people's research on intangible cultural heritage has gradually transitioned to industrialization. This article aims to study the influence of wireless communication using embedded microprocessors on the industrialization of intangible cultural heritage products and aims to help the industrial development of intangible cultural heritage products through in-depth understanding of wireless communication. This article puts forward the relevant knowledge of the MIMO system, by introducing the operating process of the wireless communication of the embedded microprocessor, the necessity of the industrialization of intangible cultural heritage products, and the relevant knowledge of how to commercialize it; finally, the industrialization development model of intangible cultural heritage under the support of new technology is drawn. In the experiment, this paper discusses the application of wireless communication technology of embedded microprocessor in the design of intangible heritage products and, based on this, discusses the road of industrialization of intangible heritage products assisted by wireless communication. Finally, the experimental results of this paper show that compared with traditional intangible cultural heritage products, the popularization rate of intangible cultural heritage products produced by wireless communication technology of embedded microprocessor has increased by 15–20%. [ABSTRACT FROM AUTHOR]

At present, the industrial Internet has gradually become a product of the integration of new generation of information technology and manufacturing. The development of the traditional manufacturing industry with transformation and upgrading faces various bottlenecks. These bottlenecks require the industry to make technological improvements through the concept of promoting sustainable development. At the same time, these issues also need intelligent support to match them. IoT technology can help enterprises realize product design and production, inspection and testing, risk early warning and post-sales, and other process links. The Internet of Things technology improved and innovated the industrial production process in the process. This technology has become the main means to promote industrialization and information integration, and it is an important basis for promoting manufacturing capabilities and networking forces. At present, the industrial Internet of our country is generally developing rapidly. However, this technology encountered many difficulties in the process of promoting discrete manufacturing and upgrading. There are still some difficulties in the entire technology landing application process. For example, there is still a significant gap in the breadth and depth of the Internet of Things applications. In particular, the value of data needs to strengthen. Based on the analysis of the risk solutions and development dilemma of artisanship, this article shows the benefits of the Internet of Things technology. Trend demand, practical application demand, production efficiency demand, after-sales service demand, and other aspects promote management innovation. This article first classifies the development of the industrial Internet in information transmission and development of the industry around the world. On this basis, this article has built a three-dimensional reference model for the industrial Internet to promote the transformation and upgrade of discrete manufacturing. In addition, this article proposes a strategy to promote the transformation and upgrade of discrete manufacturing. It includes three development stages: industrial Internet, industrial and commercial Internet, and industrial intelligence Internet. On this basis, the text explains the corresponding technical system and its challenges. Through the research results of this article, it provides theoretical guidance for the industrial Internet to promote the transformation and upgrade of discrete manufacturing. [ABSTRACT FROM AUTHOR]

International environmental law is the basic charter for dealing with international environmental issues, and it plays an important role in international environmental governance. In recent years, China's economy has achieved great development, but environmental problems are also very prominent. International environmental law provides a basic reference for China's environmental governance, but it also brings challenges to the development of China's environmental productivity to a certain extent. At the same time, due to the unique dominant position of international environmental law, it has played a certain restrictive role in the development of China's environmental productivity. Based on this, in order to promote the sustainable development of China's economy, this paper took China's industrial and agricultural development as the research object. This paper has conducted research on China's industrial and agricultural environmental productivity, aiming to explore the role of international environmental law in China's environmental productivity. The article first analyzed the limitation of international environmental law on China's environmental productivity, and then on this basis, the article conducted a numerical simulation of China's industrial and agricultural environmental productivity. Finally, starting from the actual development situation, the paper aimed to find out the numerical deviation of China's environmental productivity changes through quantitative analysis. In the course of the research on environmental productivity development, the article found a strong correlation between environmental productivity and international environmental law in China. The correlation between environmental productivity and international environmental law reaches 59.93% in South China and 61.02% in North China. Also, after a series of comparative analyses, the article finds that changes in climate characteristics can exacerbate the regulation of China by international environmental law and seriously affect China's economic development. In this case, China's economy declined by 2.6% year-on-year, which further pushed China to practice sustainable development strategies. This shows that it is essential to study the relationship between international environmental law and China's environmental productivity. [ABSTRACT FROM AUTHOR]

Industrial development and human resources matching can better promote economic growth. The mismatch, incoordination, and noninteraction between the upgrading of the industrial structure and human resources in the western region have severely restricted the speed and quality of regional economic development. Based on the in-depth analysis of the coupling effect mechanism of industrial structure upgrading and human resources in the western region, this paper constructs an evaluation index system for industrial structure upgrading and human resources in the western region. The coupling coordination degree model was used to calculate and analyze the coupling degree and coupling coordination degree between the industrial structure upgrading and human resources in western China. The results show that from 2009 to 2018, the industrial structure upgrade and the level of human resources in the western regions continued to rise. Before 2015, the level of industrial structure was higher than the level of human resources, and then the opposite trend appeared. From the perspective of regional distribution, the coupling and coordination of the two systems in western regions are quite different. The upgrading of industrial structure and the coordination of human resources in the three regions of Shaanxi, Chongqing, and Sichuan are generally higher than those in other regions, but there was still a gap from the high-quality coupling state. Therefore, an in-depth understanding of the coupling stage, current situation, and problems of industrial structure upgrading and human resources in western regions will help to further promote the high-quality economic development of western regions. [ABSTRACT FROM AUTHOR]

In recent years, with the development of information technology, "internet plus" has become the main way to promote the development of sports industry, and keeping the sustainable development of sports has also become the most challenging topic in the sports field. In order to solve the sustainable development of sports industry, this paper analyzes the problems of traditional sports industry in product types, marketing models and management, and applies "internet plus" to sports industry, forming new industries such as Internet broadcasting, intelligent software and hardware, e-commerce, and e-sports, realizing humanized and intelligent products, diversified organizational forms, and innovative management models. Through the connotation and classification of "internet plus sports," it integrates and analyzes the new format. The results show that the innovative development of new formats can be realized through product and business integration, product positioning optimization, and active industry guidance, and a "high+new" industrial structural development model can be formed. On the basis that the government and market mechanism do not conform to the economic development, through the optimization of collectivized industrial organization, a "collectivized" organizational model has been formed, and a new format of "internet plus" sports industry has been constructed. The research results have laid a solid theoretical foundation for the development of "internet plus sports." [ABSTRACT FROM AUTHOR]

The development and construction of cities and villages are a complex process jointly promoted by multiple subjects such as government, residents, enterprises, planners, and community elites. Through the summary and analysis of the practice of art rural construction at home and abroad, it is found that its events show three main paradigms in the development process. The environmental creation paradigm reconstructs the environmental semantics of the countryside through the creation of environmental art works, showing the remarkable characteristics of "the presence of works." The cultural revival paradigm maintains the local culture through cooperation with residents in art and has the characteristics of "de-artization " and "de-heritage." The industrial development paradigm adjusts the industrial structure through the production of commodity art to achieve the improvement of the rural economic foundation. Under the new development trend, the three paradigms are gradually converging. [ABSTRACT FROM AUTHOR]

With the fast development of the industrial Internet, its interconnectivity poses new challenges for the cooperation of industrial entities. Cooperation among these entities is built on trust, and trust is based on high-quality industrial products at reasonable prices. A traceability system can play an essential role in objectively reflecting the production process and promoting this trust. However, traditional traceability systems often have data privacy issues. Because traceability data are collected or generated during the production process (namely, production-related data), they could be considered privacy data. Several researchers have introduced privacy protection schemes into the traceability system, such as authentication or encryption. Nevertheless, when a privacy protection scheme is established, the original data are disclosed to the legal user of the system, but the data may still be leaked intentionally or unintentionally. Except for data privacy issues, a traditional traceability system can be vulnerable to network attacks, data unavailability, and reliability issues. The authors conducted a study to overcome these shortcomings, and this paper reports the results. We built a traceability prototype system using a blockchain protocol and a zero-knowledge proof method. First, we built a blockchain to record key production process data, aiming to maintain data reliability and availability. Second, through an analysis of traceability purpose using production knowledge, the traceability purpose could be divided into multiple provable statements. By introducing privacy protection through a zero-knowledge proof, the traceability process was converted to proving relative statements. Finally, the statements were validated by a smart contract that provided openness and reliability during the traceability process. Analysis has shown that our approach could meet the requirements for high security and privacy. In addition, the paper also discusses the calculation cost of the traceability process to show our work's viability. The traceability system described in this paper creates new possibilities for constructing a healthy and reliable trust relationship between production entities to provide further support in the development of the industrial Internet. [ABSTRACT FROM AUTHOR]

The development of wireless communication and the Internet of Things has promoted the construction of smart cities and is the technical basis for the construction of smart cities. The influence of regional economic development level on smart city construction cannot be ignored, and it constitutes the external environment of smart city construction. The combination of the two will play a driving role in the construction of smart cities. Therefore, the planning and construction of smart cities must be coordinated with the realization of the two. This paper adopts a combination of literature analysis and field investigation to analyze the decoupling between smart city construction and regional economic development, conduct research on relevant cities, and combine the current situation of smart city construction to collect the problems encountered in smart city construction and regional economic development. Through analysis, it provides suggestions for the development of smart cities and regional economic development. The survey results show that in the process of smart city construction and regional industrial economic development in the context of the Internet of Things, information security and lack of talent are the most prominent problems. Among the relevant suggestions on these issues, the proportion of talent introduction is about 45%, and the proportion of rational planning of industrial structure is about 28%. Based on the experience of existing research results, this study uses optimization algorithms to make the impact of various factors more specific, which is helpful for each region to make scientific planning based on its own actual situation. [ABSTRACT FROM AUTHOR]

In order to explore the analysis and research on the development of digital industry and further understand the industrial development trend, in view of the continuous growth of the scale and quantity of digital industry and the continuous increase and expansion of digital industry economy, this paper uses the most popular intelligent deep learning algorithm to verify and research the efficiency of digital industry development under intelligent technology. Finally, it is considered that the application of intelligent deep learning algorithm not only meets the development needs of digital industry in the intelligent era but also improves the accuracy of economic development of digital industry and the overall development power. It has important strategic significance in promoting the economic prosperity of digital industry in the later stage, improving the advantages of industrial development and improving people's livelihood, and has a new awareness of China's economic development in the world. [ABSTRACT FROM AUTHOR]

The cultural construction in the process of industrialization is intertwined with the culture required by the development of green manufacturing industry, which has become the growth point of economic construction and the new trend of economic development. Efficiency is the basis for the development of various industries. If we do not improve efficiency, industrial development will cause waste of resources and environmental pollution. Therefore, this study proposes a new evaluation method of green industrial manufacturing efficiency. The proposed method suggests cultural enterprises. In addition, this study examines the cultural green manufacturing industry productivity of cultural enterprises and combines it with machine learning. The excellent performance of neural network in prediction makes it possible to predict the efficiency of green manufacturing industry of cultural enterprises. Genetic algorithm is also proposed to optimize BP network. This algorithm is easy to operate and requires few parameters. In the process of finding the optimal solution, the optimal individual in the group can be used to control the iterative process. The particle swarm optimization algorithm is improved and combined with genetic algorithm to get an improved hybrid algorithm. BP network is optimized, and an improved BP network prediction model is established to evaluate the efficiency of green manufacturing industry of cultural enterprises. A large number of experiments have proved the effectiveness and reliability of this method. Separate simulations and results are presented to verify the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

The Chinese sports industry encompasses both the secondary and tertiary sectors of the country's economy. More prominent are the issues of unbalanced industrial structure development, mismatch between supply and demand, and rapid expansion of the sports goods manufacturing industry. This paper first employs the literature method to investigate the dynamic mechanism and promotion strategy of China's sports industry's green development. In order to improve the accuracy of data mining and quantitative analysis in the sports industry, this paper proposes a time series-based model for the analysis of sports industry data. Utilizing the global steady-state feature fusion method, the statistical and quantitative fusion analysis method, and the fuzzy analytical control method, accurate mining of sports industry data is achieved. The simulation results demonstrate that this method has greater precision and a higher degree of feature matching for sports industry data mining, thereby reducing the disturbance error of sports industry data mining. [ABSTRACT FROM AUTHOR]

In ethnic minority areas, the rich cultural color has strong attraction and market competitiveness. While making full use of it to promote the local economic development of ethnic minorities, it promotes the inheritance and protection of ethnic culture and the cultural exchange and integration among multiethnic groups. In this case, a new data mining (DM) technology came into being. DM is a new data processing technology for developing information resources. The object of DM is not only a database but also a file system, or any other data collection organized together. Based on DM technology, this paper studies the industrialization innovation of ethnic minority cultural and artistic resources, which carries out DM on the basis of rational utilization of ethnic minority cultural resources, boldly innovates, uses new scientific and technological achievements and new artistic expression means, establishes the people-oriented service concept of cultural and artistic resources, and takes the individual needs of the public and the scientific analysis results of big data as the basis to provide a satisfactory and ideal cultural and artistic feast for the public. [ABSTRACT FROM AUTHOR]

In order to pay attention to the protection of the third tier industrial heritage, this paper puts forward the protection measures of combining the third tier industrial heritage with tourism based on the concept of urban image. The tourism value of the tertiary industrial heritage is evaluated by using the comprehensive evaluation method. Through the analysis of the tourism value evaluation system combining the three-level industrial heritage and rural tourism in a certain city, the following conclusions are drawn. In the comprehensive evaluation layer, the value of the third tier industrial heritage accounts for the largest weight of 0.5581, indicating that the third tier industrial heritage resources occupy an important position in the third tier industrial heritage tourism value system. Tourism development conditions also account for a large proportion, which explains that while adhering to the principle of third tier industrial heritage protection, we should pay attention to the consideration of tourism development conditions. It once again emphasizes the importance of the third tier industrial heritage for the development of industrial heritage tourism and the significance of the protection of the third tier industrial heritage for tourism development. In the three-level evaluation layer of industrial heritage and rural tourism, the historical and cultural value and social and cultural value have the largest weight. They are the leading factor of the combined value of tertiary industrial heritage and rural tourism. Historical and cultural value is one of the important meanings of three-level industrial heritage protection and also the essence of the combined development of third-level industrial heritage tourism and rural tourism. Social value determines the recognition of tourists and people to participate in the development of tourism. In the evaluation layer of tourism development conditions, the development potential is particularly prominent. The development potential is the characteristic of the third tier industrial heritage tourism of a city. The development of the third tier industrial heritage tourism of a city must be combined with the local characteristics to highlight the differences. [ABSTRACT FROM AUTHOR]

The first motive force of development is innovation. If we want to enhance the driving force of industrial development, we must transform the achievements of scientific and technological innovation effectively. Developing strategic emerging industries is one of the most important tasks of our country now. The combination of machine learning and PCA financial support is very important for the transformation of military scientific and technological achievements (STA) in China. Based on PCA, this paper selects some representative input-output indicators. According to the survey, China's strategic resource allocation has an impact on emerging industries, and there is room for optimization. The form of ownership of a company, whether it holds two positions concurrently, the financial results, and the rights and interests of some shareholders have obvious bad effects on comprehensive efficiency, while the time of establishment and the location of the company have obvious good effects on comprehensive efficiency. [ABSTRACT FROM AUTHOR]

This paper tries to investigate the future development tendency of five typical industries in China and find out whether there exists a different innovation strategy preference between Chinese firms of low- and high-knowledge density industry in the background of low-carbon sustainable development. First, this paper finds that the innovation driven-based trend of industrial development is further accelerated in China. Firms in industries with high knowledge and technology density, such as specialized-supplier, scale-intensive, and science-based industries, are more likely to choose exploratory innovation strategy than exploitative innovation strategy. Firms in industries with low knowledge and technology density like service- and supplier-dominated industries are more likely to choose the exploitative innovation strategy. Second, results indicate that exploratory innovation can bring higher technological innovation performance than exploitative innovation. And the effect of the ambidextrous strategy is better than the single exploitative strategy in industries with high knowledge and technology density like specialized-supplier, scale-intensive, and science-based industries. Third, this paper suggests that innovation strategy preference plays a mediating role between industry type and technology innovation and a moderating effect of knowledge management capacity between innovation strategy and firms' technology innovation. [ABSTRACT FROM AUTHOR]

China's coast is the main spatial carrier and important geographical unit for future industrial development in China. We propose a weighted average decomposition method based on three basic problems in the theory of SDA model decomposition method, investigate the relevant properties of this method, and prove that two decomposition methods widely used in the literature—bipolar decomposition method and midpoint power decomposition method—are the approximate solutions of this decomposition method. Based on the idea of the Wasserstein distance algorithm for machine learning, the Wasserstein distance algorithm and its solution are improved by using the matrix expansion Sinkhorn algorithm and the entropy regularization constraint method, and the industry copolymerization index is constructed through hypothesis testing and Monte Carlo simulation to measure the level of industry copolymerization in coastal China. The results show that the level of industry copolymerisation within the same quantile industry is greater than that between industries across quantile industries in China's coasts. [ABSTRACT FROM AUTHOR]

Logistics distribution vehicle scheduling plays an important role in the supply chain. With the wide application of e-commerce technology and the increasing diversification of urban industrial and commercial development mode, the optimal scheduling of logistics distribution vehicles can improve the economic benefits of logistics and realize the scientization of logistics. Aiming at the problems existing in the logistics allocation system, this paper proposes a logistics allocation system model based on a heterogeneous neural network, uses the heterogeneous neural network to optimize vehicle scheduling, and gives the specific steps to solve the problem of optimal scheduling of distribution vehicles. The simulation consequences exhibit that the proposed technique cannot solely efficaciously clear up the automobile scheduling optimization model and however additionally has low pc complexity, excessive computational effectivity, and speedy convergence speed. The practicability and effectiveness of the improved algorithm are verified. When the number of distribution customers and distribution cycle is the same, the proposed algorithm effectively reduces the total distribution mileage, reduces the number of vehicles, and improves the efficiency of logistics distribution. [ABSTRACT FROM AUTHOR]

World heritage is a kind of affirmation and high honor given by the international community to the important civilization, historical relics, or natural landscape of a country and nation. This paper studies and analyzes the sustainable development of heritage tourism boosted by smart tourism based on big data artificial intelligence. This paper first analyzes big data and then introduces the concept of smart tourism. Smart tourism is a new future-oriented tourism form that serves the public, enterprises, and governments. It uses the Internet of Things, cloud computing, next-generation communication network, high-performance information processing, intelligent data mining, and other technologies in tourism experience, industrial development, administrative management, and other applications, so that tourism physical resources and information resources have been highly systematically integrated and deeply developed and activated. And then, we analyze and discuss artificial intelligence algorithms. Artificial intelligence is a new technological science that is researched and developed on the basis of computer science as a simulation and extension of human intelligence activities. Finally, a comprehensive analysis is made on the tourism ecological footprint of natural heritage sites and the carrying capacity of tourism ecology in natural heritage sites. The experimental results of this paper show that the tourism development of this natural heritage site is in a sustainable state. The reasons are as follows: First, the average tourist ecological footprint of the place is 0.009466 hm2, the average tourism ecological carrying capacity is 0.032861 hm2, and there is an average ecological surplus of 0.02339 hm2; secondly, the average tourist natural footprint is 18285.93 hm2, the average tourism environmental carrying capacity is 40421.97 hm2, and the average ecological surplus is 22136.04 hm2. To sum up, it shows that its tourism development is in a state of sustainable development. [ABSTRACT FROM AUTHOR]

With the gradual advancement of informatization and industrialization, the safety and controllability of industrial Internet of things (IoT) have attracted more and more attention. Aiming to improve the security of industrial IoT, a detection method using stacked sparse autoencoder network model is proposed. In this method, the basic units of the network model have been simplified and sparse, and some of basic features are combined with obtaining a higher-level abstract expression, so as to solve the problem of unbalanced network traffic data. The cascaded network structure is adopted to stack its sparse autoencoder network model, so as to improve the data ability of the detection model. In addition, the incorporation of Softmax classifier realizes the dynamic adjustment and optimization of the whole network parameters, which further ensures the efficiency of the detection method. The simulation experiment is based on NSL-KDD dataset. The experiment has proved that the proposed method has excellent network attack identification and detection performance. Its accuracy index is about 95.42%, and the detection time is about 3.42 s. [ABSTRACT FROM AUTHOR]

With the gradual integration of the Internet into people's daily life and the increasing number of students and organizations joining the Internet wave, more and more people begin to carry out entrepreneurial activities by taking advantage of the rich resources, sharing, and communication characteristics of the Internet. No matter ordinary people or outstanding social elites, they can develop their own innovation and creativity at all levels under the influence and role of Internet informatization. University students' innovation and carving out are one of the vital methods to alleviate the strain of social employment and industrial transformation and development; however, the lack of entrepreneurial high-quality and bad integration of social sources also has an effect on the success of university students' innovation and carving out. To resolve the above problems, this article constructs a digital platform for innovation and carving out cultivation undertaking in schools and universities primarily based on smart analysis. Digital-wise evaluation can successfully promote the data administration of the platform, overcome the inherent troubles such as old-fashioned records sources and gradual updating of regular platforms, make full use of the advantages of large data, combine scan and theory, and assemble a remarkable varied ecological environment. Within the functional scope of the platform, provide innovation and carving out information resources for users in need, enhance the clever processing stage of innovation and carving out facts in schools, recognize the adaptive scheduling of innovation and carving out facts, minimize the work depth of innovation and carving out records managers, enhance the deployment effectivity of innovation and carving out data in faculties and universities, and domesticate the innovation and carving out capability of university students in an all-round way. Promote the innovation and improvement of innovation and carving out things to do in universities. [ABSTRACT FROM AUTHOR]

Automation in industries offers the benefits of enhancing quality and productivity while minimizing waste and errors, raising safety and adds stability to the production process. Industrial automation offers high profitability, reliability, and safety. It is beneficial to employ machine learning in the field of industrial automation as it helps in monitoring and performing maintenance on industrial machinery. Rational industrial development is closely associated with efforts for automating industrial techniques in all existing ways. Latest improvements in the automation of industrial systems resulted in decrease in cost of energy consumption and hardware. The proposed system is dealt with deep learning–based soft sensors for automation of industrial processes. The eminent benefits of soft sensors are versatility, flexibility, and low cost. With deep learning, many number of features could be processed. Thus, deep learning–based soft sensor encapsulates the above benefits. Soft sensors offer another way for the measurement of process variables, which are measured offline. Deep learning techniques are famous in the design of soft sensors for tough nonlinear systems due to the robustness and accuracy. The work depicted here designs a soft sensor based on deep learning algorithm for automation of industry. In the proposed system, a soft sensor contemplated on deep learning such as the deep neural network (DNN) is presented. The application of deep learning–based soft sensors in the automation of some industrial processes is also discussed here. The proposed system is tested on automatic control on solar power plants and in the measurement of reactive energy in industries. It was found that the proposed system yielded better results with its application in the automated industrial processes. [ABSTRACT FROM AUTHOR]

A field experiment was conducted in 2018/2019 growing season at the Scientific Industrial Research and Development Center under irrigated conditions using the simple alpha lattice (7 ∗ 7) design, with three replications. The objective of the study was to determine the performance of 44 elite rice lines that were selected and shared from elite doubled haploid germplasm and five cultivars were used as checks. All evaluated genotypes exhibited significant variation in the traits measured except for number of grains/panicle, total tillers/plant, and effective tillers/plant. Elite line 70462 was found to be the highest yielding, with yield advantage of 66% over the high yielding local check (Nerica 7). High values for broad sense heritability were recorded for days to 50% heading, panicle length, culm length, number of filled grains/panicle, 1000-grain weight, grain length, grain shape, and grain yield and indicated lesser influence of environment in expression of these traits, hence amenable to simple selection. Correlation analysis revealed that grain yield manifested significantly positive correlation with filled grains/panicle contributing the highest correlation (r = 0.784), followed by culm length (r = 0.605), spikelet fertility/panicle (r = 0.677), grain length (r = 0.551), 1000-grain weight (r = 0.518), panicle length (r = 0.449), and number of grains/panicle (r = 0.328). Based on grain yield, number of filled grains/panicle and spikelet fertility/panicle, panicle length, and earliness, lines 70462, 60143, 70383, Arica 3, Sahel 177, 6040, 70537, 60409, and 70476 had the best performance. Selection of these traits would be more effective for yield improvement in rice and these promising lines could be used in the varietal development and can be tested in multilocational trials and on-farm trials in Zimbabwe with the possibility of release and commercialization. [ABSTRACT FROM AUTHOR]

Green has become the underpinning of High-quality development in China. Green development is inseparable from the support of institutional governance. This study uses MVC mode to build institutional governance mechanism, and constructs institutional governance system and model of regional green development. The empirical results show the following: institutional governance has great influence on industrial green development. From the perspective of China's provincial industrial green development, Shandong Province has been maintaining the first position of governance investment. Green governance is better in southern China than in the northern provinces. And the institutional governance intensity of each province is not evenly distributed. Therefore, China's industrial green development still needs to further strengthen the system governance of northwest and northeast regions. Finally, this paper aims to improve the green development level of China's regional industrial economy through the construction of institutional governance system. It provides institutional environment for the development of green innovation. [ABSTRACT FROM AUTHOR]

With the development of global economy, the evaluation of industrial clusters has become an important method to scientifically analyze the advantages and disadvantages of industrial development. The current research model uses the traditional evaluation method, which leads to the problem of unsatisfactory evaluation results and low effect. This paper proposes an evaluation model based on the BP neural network combined with the LM algorithm, which has the advantages of fast convergence speed and strong application ability. The comprehensive evaluation model of industrial clusters is put forward from the comprehensive application of the scale, benefit, and 27 related evaluation indexes of industrial clusters. This paper takes Beijing, Tianjin, and Hebei industrial clusters for BP-LM evaluation and analysis, which fully illustrates the advantages of this method. The evaluation results show that the evaluation target value and the average error of the overall parity have obvious advantages compared with those of other models, which provides application guidance for local economic development and policy formulation. [ABSTRACT FROM AUTHOR]

The development of industrial Internet platform is an important carrier to realize the innovation of Industry 4.0. This paper analyzes the development mechanism of Chinese industrial Internet platforms from three aspects of motivation, incentives, and constraints, summarizes the influencing factors of platform development, and establishes a growth model of industrial Internet platform, to select representative factual data as observation variables to verify the effect of each factor. In the end, this paper puts forward relevant suggestions for the government, platform companies, and other related parties to drive the realization of Industry 4.0. [ABSTRACT FROM AUTHOR]

The insufficient innovation ability is the biggest bottleneck for the upgrading of creative industry in China. Thus, it is an important way to structure the good R&D innovative ecosystem around perfecting the innovative chain for improving the innovation ability of creative industry. This paper discusses the theoretical connotation of the R&D innovation ecosystem of creative industry, studies the spatial structure of the R&D innovation ecosystem, and proposes the fact that the innovative population of R&D innovation ecosystem in creative industry can be divided into original innovative population, technological innovation population, innovation service population, innovation input population, and system innovation population. The research on the demand, financing, and business model of R&D breakthrough innovation in China's industry cannot be separated from the analysis of the evolution stages of various industries, because different strategies need to be formulated at different stages of development, and it is very important to accurately grasp the stage of industrial development. By introducing logistic curve equation, the breakthrough innovation of industrial R&D is divided into four stages: incubation stage, growth stage, evolution stage, and maturity stage, and the different characteristics of different stages of industry development are analyzed. Taking the breakthrough innovation of R&D in industry as an example, this paper uses the logistic empirical model based on factor analysis to study it. The results show that the breakthrough innovation of R&D in industry has entered a maturity stage. [ABSTRACT FROM AUTHOR]

In this era of developed network communication, this paper analyzes the development prospect of industrial economy based on mobile information systems. Firstly, this paper compares and analyzes the relationship between the information industry and industrial economics, constructs the framework diagram between them, then establishes the VAR model to simulate the industrial economy, statistically compares the industrial economies from 2005 to 2016, and finally uses the impulse response function to correct and calculate the data results. This paper deeply analyzes the industrial economy based on mobile information, compares enterprises and small assets, studies the evolution and development law of traditional industries based on mobile information, summarizes the impact of "modular" manufacturing on the production organization of information companies, and reveals the "virtual vertical integration" of information industry manufacturing enterprises. The data show that most of the industrial economy in the first 10 years has a downward trend, with a small increase, but it is not obvious. Finally, it is concluded that the industrial economy will show a downward trend in recent years, and the annual downward trend is about 5%. [ABSTRACT FROM AUTHOR]

Summary: Energy plays a pivotal role in industrial development of any country. At present, most of the countries are utilizing fossil fuels, mainly coal and natural gas as energy sources for power production. However, these sources emit high amounts of carbon dioxide (CO2) into the atmosphere resulting in global warming. Hence, the fossil fuel–based thermal power plants need to be integrated with CO2 sequestration and utilization processes for sustainable power production. In this work, four natural gas combined cycle (NGCC) power plant configurations are proposed—two with CO2 capture and sequestration (single and double calcium looping units) and two with CO2 capture and utilization (for production of dimethyl ether). Energy, exergy, environmental, and economic analyses are carried out to assess the performance of the proposed novel configurations against the conventional NGCC power plant. These analyses reveal that the NGCC power plant integrated with double calcium looping unit captures 91.32% of CO2 with an energy penalty of 6.73%. The proposed CO2 capture and utilization integrated configurations have low electrical power output; however, the conversion of CO2 to high energy density dimethyl ether (DME) product resulted in overall energy and exergy efficiency gain. The CO2 capture and utilization configuration integrated with solar energy is able to convert the total captured CO2 to DME and makes the process sustainable. [ABSTRACT FROM AUTHOR]

The building materials used by mankind in the past, such as stone, soil, and wood, have been environment-friendly. However, the various building materials invented over time with the development of the industrial age pose problems such as environmental hormone generation and waste generation/disposal. To overcome these problems, building materials based on soil, a traditional building material, are being developed by researchers. However, the improvement in soil's structural characteristics is insufficient as it excessively emphasizes efficacy and function only. In this study, lime and Dobak-glue were mixed with soil to solve the structural problems and improve the strength of soil, and water content and change in strength in accordance with curing time were tested. In order to understand the change in strength, a compaction test was performed by preparing a standard specimen based on the optimum water content and maximum dry density. The lime mix required optimum water content and quantity of lime equal to 3% of soil weight, while the Dobak-glue mix was prepared by soil mixing in the same weight ratio as optimum water content. Changes in water content and compressive strength were measured over curing time of 3, 7, and 28 days. Three specimens, lime mixed specimen, Dobak-glue mixed specimen, and standard specimen, were prepared, and their water content and compressive strength values were averaged. Although the change in water content according to the curing period differed depending on the material mixed with soil, there was no significant difference between 7.12% and 2.82% after 7 days. As for the change in compressive strength, the initial compressive strength in lime mixed specimen was excellent, but the Dobak-glue mixed specimen displayed the greatest strength after 7 days. To conclude, Dobak-glue is an eco-friendly material, and it can be very useful in compensating for the structural shortcomings of soil. [ABSTRACT FROM AUTHOR]

In recent years, the process of industrial modernization has intensified, traditional industrial control has been improved and rapidly developed, industrial automation and intelligent unmanned production lines have become a new development trend, and the Internet of Things has become the basic direction of industrial development. In order to improve the effect of safe transmission and industrial IoT traffic detection, this study uses a neural network to improve the industrial IoT traffic detection algorithm. In order to improve the visualization effect of monitoring, this study uses computer vision technology to construct a traffic detection system of secure transmission industrial Internet of Things and builds an intelligent detection model. Finally, this study combines experimental research to verify the performance of the system. From the statistical point of view, it can be seen that the system's security detection and traffic detection effects are very good. [ABSTRACT FROM AUTHOR]

In order to study the driving force of China's rapid economic development in the past ten years, the study takes Guizhou, Yunnan, and Guangxi as a case study, focusing on the big data assets exchange (GBDEx) and Beibu Gulf Economic Zone, and discusses the impact of Internet plus economic and government data and the big data system on regional economy. Finally, it is believed that the Internet and big data fully avoid the disadvantages of traffic distance between the western region and the eastern region, make full and efficient cooperation between enterprises and institutions in the central and western regions and Chinese and foreign economic entities, and strengthen the control of economic behavior from the big data level with the support of the service-oriented government. The information entropy output from the Internet big data system has led to a significant entropy reduction process in China's economic environment and a more orderly economic system, which is also an important reason for the rapid development of China's economy. [ABSTRACT FROM AUTHOR]

Based on the dual perspective of input-output and network analysis, this study takes typical industrial sectors of China's entertainment industry as representatives. Through the input-output analysis of industrial correlation characteristic indicators and construction of an industrial correlation network, we conduct a systematic and quantitative study on the entertainment industrial correlation characteristics and structural characteristics of the industrial correlation network in China. Furthermore, we clarify the role of the entertainment industry in China's industrial development and its positioning in China's whole industrial correlation network. We have the following key findings: China's entertainment industry as a whole shows the characteristics of final demand-oriented industries, whose rapid development plays a certain positive role in boosting consumption and driving economic growth. Within the whole industrial correlation network in China, there is frequent interaction between the entertainment industry and other industry sectors within the directly related network; it will especially exert obvious radiation and driving effect on the upstream industry. However, limited by the scale of the direct industrial correlation network, such influence is still difficult to achieve the common development of most industries in China. [ABSTRACT FROM AUTHOR]

With the outbreak of the new crown epidemic, the world economy has been severely tested, making predictions more difficult. Wireless sensors have the advantages of low cost, ease of use, high reliability, and high safety and have been widely used in the tourism economy. In order to understand the ability of wireless sensors to predict the regional economy, this article uses an example to construct a nonlinear model of wireless sensors to predict the regional economy. With the continuous development of the concept of circular economy, circular economy has gradually been recognized by Chinese scholars and practitioners. After domestic scholars continue to study the theory of circular economy, practicing the concept of circular economy and taking the road of sustainable development have become one of the important directions of the development of industrial theory. Literature analysis and other methods were used to conduct research on databases such as CNKI, Wan fang Database, and SSCI. Literature was collected, and GIS spatial analysis technology was used to analyze different areas and finally get a prediction model. The phenomenon is nonlinearity (such as saturation nonlinearity in the magnetic circuit), and some are caused by the nonlinear relationship between system variables (such as linear resistance and squared nonlinearity between current and power) and some artificially introduced nonlinear links (such as the hysteresis nonlinearity of relays). Experiments have proved that there is a certain error between the prediction model and the actual result; the error value is about 9%, which is less than the value of other prediction models. This shows that the output results of the nonlinear model of wireless sensor regional economic prediction should be processed reasonably. This result has a certain reference value, and its output should be combined with the actual situation. Related research found that under the nonlinear model, the more accurate and comprehensive the input value is, the closer the output result is to the actual value. [ABSTRACT FROM AUTHOR]

We wish to credit our own Research Integrity and Research Publishing teams and anonymous and named external researchers and research integrity experts for contributing to this investigation. This article has been retracted by Hindawi following an investigation undertaken by the publisher [[1]]. [Extracted from the article]