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In the vision of smart cities, everything is highly connected with the aid of computational intelligence. Therefore, the cyber-physical society has been named a computational social system for a long time. Due to the high relation with vast populations' national livelihood, agriculture will still serve as a core industry in the national economy. As a result, this study focused on an efficient forecasting method for the agriculture economy. In recent years, the conception of deep intelligence has received overall prevalence in academia because of its excellent performance in implementing intelligent information processing tasks. Hence, this paper utilized deep intelligence driven by neural networks and managed to investigate an efficient prediction method for the agriculture economy of computational social systems. To fit the time-series forecasting scene of the long-term development of the agriculture economy, the convolutional neural network model is slightly improved by revising its parallel structure into the recurrent format. Finally, simulations on realistic datasets are carried out to evaluate the proposed forecasting method., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Xuelan Li et al.)

In this paper, we proposed an assessment system of forest environmental carrying capacity from many aspects and comprehensively evaluated and predicted the forest environmental carrying capacity of 40 cities in the Yangtze River Delta of China by using the proposed deep learning-based model. In addition, the proposed model is used to dynamically evaluate the comprehensive scores of forest environmental carrying capacity of 34 provinces and cities in China between 2015 and 2020. This paper also has the following contributions: (1) a deeply integrated unidirectional bidirectional LSTM considering the correlation of time series is proposed. The bidirectional LSTM network is used to deal with the backward dependence of input data to prevent the omission of some useful information, which is beneficial to the prediction results. (2) In terms of missing data processing, the Mask layer is added to subtly skip the processing of missing data, which will help to enhance the evaluation results., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Song Linshu et al.)

Urban green ecological space is an important manifestation of the environmental characteristics of a green city. The research results show that the urban green ecological space has obvious cooling and humidity effects, which are very important for reducing the urban heat island effect. Remote sensing technology describes the slow-release effects of urban green parks in different seasons from the two perspectives of thermal slow-release intensity and thermal slow-release distance. In this paper, UAV remote sensing is used to extract the internal and external factors of the urban green environment characteristics and to identify the main factors that affect the slow-release heat effect and seasonal changes of the urban green environment. In addition, it analyzes the factors that affect the urban environmental temperature within the environmental temperature slow-release range of urban green space, establishes a model to predict the environmental temperature within the thermal slow-release range outside the park, and realizes the largest thermal slow release in the urban greening ecological space. These are new technologies created in the context of digitization, which include image understanding and synthesis, which involve the use of computer graphics and image processing technology to convert data into graphics or images displayed on the screen to achieve an interactive process., Competing Interests: The author declares that there are no conflicts of interest., (Copyright © 2022 Wenpeng Zhang.)

During the development of the urban water system from 1.0 to 3.0, the impervious surface area gradually increased, hindering the natural infiltration and self-purification process of urban rainwater, resulting in serious urban water pollution, urban waterlogging in the rainy season, and groundwater problems. Since water will seep into the ground, serious water pollution will cause damage to the ground. Therefore, in dealing with urban rainwater problems, we want to use the sponge's ability to absorb and store water to build our cities into sponge cities. In this paper, we have constructed a sponge city planning and information system development based on geographic information fuzzy processing. We use differentiated fuzzy processing methods to eliminate classified information to achieve a perfect combination with nearby images and use ordinary fuzzy processing methods to solve the problem of nonconfidential information. This paper discusses the impact of natural topography on the planning and construction of sponge cities, including whether natural topography will affect rainwater, whether it will affect the distribution of different strata, and whether it will affect the utilization of groundwater resources. The basic functions of this platform are provided by a series of functions of GIS, and multiple modules are developed according to management requirements. The initial state of street view data is a lot of fisheye lens photos and corresponding point location information, which are displayed online after data preprocessing, detection information, editing information, and blurring processing., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Mingxin Gan and Tongfang Li.)

Synergistic development is the only way which must be passed and a key point to achieve high-quality economic development. This paper regards regional synergetic development as a composite system, builds up the evaluation indicator system, and calculates the level of economic synergetic development of Guangdong-Hong Kong-Macao Greater Bay Area Urban Agglomeration, by using the collaborative degree model of composite system. The results show that each subsystem of the composite system has a high degree of order from 2007 to 2019, but compared with Beijing-Tianjin-Hebei urban agglomeration and Yangtze River Delta urban agglomeration, the level of economic collaborative development of Guangdong-Hong Kong-Macao Greater Bay Area urban agglomeration in 2008-2019 is relatively low and has large spatial differences. The main reason is that under the background of "one country, two systems" policy, the institutional differences between Guangdong, Hong Kong, and Macao have not been effectively linked up and synergetic, Greater Bay Area urban agglomeration has not yet formed an organic whole, and the synergy effect of mutual support and promotion is relatively weak. Based on this, we should seize the great historical opportunity of the construction of Guangdong-Hong Kong-Macao Greater Bay Area, accelerate the construction of the mechanism for the synergetic economic development of the three areas, accelerate the establishment of an integrated market, build a reasonable division of labor system and collaborative innovation system, and jointly promote the synergetic economic development of Greater Bay Area., Competing Interests: The author declares that there are no conflicts of interest., (Copyright © 2022 Juan Yang.)

Cities are gradually developed on the basis of adapting and transforming the natural environment. In a certain urban area, human activities, natural environment, and other factors and their mutual influence constitute the urban ecological environment. Therefore, the evaluation of urban ecological environment quality is of great significance to the analysis of urban development. This paper takes a city in Western China as the evaluation object, uses AHP to determine the index weight, reasonably analyzes the current situation of the urban ecological environment, and further comprehensively evaluates the quality of the urban ecological environment. The study shows that from 2013 to 2018, the comprehensive capacity of the city's ecological environment quality showed a steady upward trend, except that the natural disasters of floods and mudslides in 2014 had a certain degree of fluctuation. The comprehensive index of ecological environment quality has increased from 0.337 in 2013 to 0.412 in 2018. The overall level is still low, but the development speed is relatively stable. The urban ecological environment has been gradually improved, and society, economy, and nature have maintained a certain degree of sustainable development., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Liang Zhou.)

With the rapid development of soft computing technology, various models and comprehensive analysis methods are emerging one after another, and new theories and research results continue to emerge, showing great strength and development potential in actual theoretical research and engineering applications. This paper analyzes the air pollution detection and environmental responsibility of sports clubs based on RBF neural networks, constructs the corresponding neural network algorithm, and simulates and analyzes the data. In the process of simulation design, we adjust the weight and threshold of the network according to the error performance of the network to realize the functions required by the system. Different models were used to predict the concentration of air pollutants in typical cities. At the same time, a meta-analysis method was used to conduct a preliminary discussion on the impact of air pollutants on the health of the Chinese population, and some research results were obtained. In the past years, Chinese sports clubs have also built a solid social environmental protection system around the related environmental protection responsibilities of sports clubs. The research on green environmental monitoring has improved people's awareness of environmental responsibility and provided technical support for the green development of sports clubs., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Zijian Guo et al.)

With the gradual improvement of material living standards, people have higher and higher requirements for the livability of modern cities. As an important component of urban construction, the optimal layout of street public space has gradually received more and more attention. In the development stage of the new era, it is very important to improve the image of the city by transforming the street construction, optimizing the urban public space, and building a place full of vitality. Implementing the people-oriented connotation and improving the green travel components in the city, such as encouraging walking and increasing bicycles, are of great significance for optimizing the street public space. This article studies the relevant content of the optimization design of street public space layout based on the Internet of Things and deep learning and expounds the solutions for the optimization design of street public space layout based on the Internet of Things and deep learning. Design research provides cutting-edge scientific theories and evidence. This paper uses data to prove that based on the Internet of Things and deep learning technology, the optimized design of street public space layout has increased the latter's recognition among residents by an average of 21.7%. The designed model has both space utilization and environmental protection. Very good results have been obtained., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Shanshan Yu et al.)

The weights of green finance indicators are established in accordance with the AHP in order to suggest an evaluation system that is more thorough and reasonable and to construct an evaluation index system. The findings indicate that the growth of urban green finance is more closely correlated with the development of environmental protection businesses, capital allocation efficiency, and governmental and social capital support. Regulation of consumption also has a significant impact. In order to encourage the growth of urban green finance, this paper analyzes the scoring outcomes and changes for each city and offers solutions and recommendations., Competing Interests: The authors do not have any possible conflicts of interest., (Copyright © 2022 Ke Wang.)

The smart city is an emerging concept that is based on the integration of various electronic devices and citizens that enhance the flow of information. IoT is an integral part for next generation wireless network infrastructure for acting as an interface of collecting data and controlling delivery of message which are using in smart cities. In this paper, an IoT-oriented relay assisted MIMO for beyond the fifth-generation wireless network system is proposed. The proposed system provides higher capacity and lower BER. The proposed system's BER results are compared with various combinations of transmission and receiving antennas at source, relay, and destination. It is found from BER performance that the developed scheme with relay does provide 1-17 dB gain with respect to direct connection. It is also found from mathematical analysis and simulation results that this scheme provides 3 to 9 b/s/Hz improvement in performance of capacity at 5 to 10 dB by adding a different combination of STBC and VBLAST. Simulation results are also presented to demonstrate the diversity and multiplexing gain that is a key to providing high data rates with reliable communication with many interferences for the IoT system. This system can also be used for massive antennas-based IoT system by raising the number of transmitting and receiving antennas with proposed encoding and decoding techniques explained in this paper., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 M.M. Kamruzzaman et al.)

The occurrence of crime has always been the main problem affecting urban public security and social security environment. Therefore, the prevention and control of crime is the focus of public security work. The traditional police strategy has poor timeliness and cannot respond and adjust in real time with the occurrence of criminal activities, and its deterrence and control of criminal activities are limited. To address the problem of low accuracy of existing crime distribution prediction models, an improved transition probability matrix for crime distribution prediction is proposed in this paper. Based on a large number of trajectory data of criminals, this paper quantitatively describes the temporal and spatial characteristics of crowd movement in different areas of the city by using the temporal and spatial transfer probability. Then, combining Markov chain and Bayes' theorem, the probability model of spatio-temporal transfer of criminal groups in regions is constructed. Finally, the model predicts the number of crimes in urban grid areas., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Junhao Zhang et al.)

Instant delivery is an intermediary bridge for same-city O2O services and an important part of urban short-distance logistics. The route planning and scheduling of instant delivery need to balance cost and customer satisfaction and consider the impact of traffic conditions on the distribution process. In this paper, we propose a vehicle routing problem model considering two types of customer time windows under time-dependent road networks and design a memetic algorithm combined with genetic algorithm and variable neighborhood search to solve the problem. By comparing the results of the different time periods and conducting sensitivity analysis for the two types of customer time windows, the effectiveness of the model and algorithm is verified., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Shuxian Cui et al.)

Global warming has become the focus of attention of the international community, and the control of carbon dioxide emissions has become one of the necessary choices for the development strategies of countries around the world. Cities are places where carbon dioxide emissions are concentrated. The key to controlling carbon emissions is to control the carbon emissions of cities. My country is currently in the process of rapid urbanization. Quantitative studies of the carbon cycle at the city level will help to take stock of carbon dioxide emissions in cities. On the other hand, it is helpful to understand the status and role of the urban carbon cycle in the process of the regional carbon cycle. Through the analysis and prediction of the elements influencing the carbon cycle of smart cities, this paper first determines the factors affecting smart cities in the carbon cycle process as industrial carbon emission strength factors, industrial structure effects, economic development factors, and population elements. It is found that the major positive factors affecting the significant add of CO2 emissions in smart cities from 2010 to 2019 are economic development factors and demographic factors, including economic development factors GDP/per capita GDP. The per capita contribution to CO2 emissions is higher than the model established by adjusting the affecting elements of overall CO2 emissions, except that the proportion of economic development factors in total CO2 emissions from 2013 to 2015 was lower than the increase in total CO2 emissions. The comparison can better reflect the relation between CO2 emissions and influencing elements. The main determinants affecting CO2 emissions are the expansion of the financial condition, the increase in the average daily population, and the increase in construction work. The adaptation index is judged to be consistent, indicating that the model adjustment effect is good; finally, the green computing in the smart city predicts the carbon cycle process, and the actual value trend line and the predicted value trend line are not much different from the practical value, the forecast error is small, and the prediction results are credible. Global warming has become the focus of attention of the international community, and carbon emission control has become one of the necessary options in the development strategies of countries around the world. Cities are the places where carbon emissions are concentrated. The key to controlling carbon emissions is to control urban carbon emissions. At present, my country is in the process of rapid urbanization. Quantitative research on the carbon cycle at the city level will help to establish an inventory accounting of urban carbon emissions. On the other hand, it is convenient to deeply understand the status and role of the urban carbon cycle in the process of the regional carbon cycle., Competing Interests: The authors declare that they have no conflicts of interest regarding this work., (Copyright © 2022 Xianghua Huang et al.)

Aiming at the problem that the road traffic flow in intelligent city is unevenly distributed in time and space, difficult to predict, and prone to traffic congestion, combined with pattern recognition and big data mining technology, this paper proposes a research method to analyze and mine the daily travel patterns of urban vehicles. This paper proposes a WND-LSTM model, which mainly includes data preprocessing, data modelling, and model implementation, to analyze the similarity of travel patterns in seasonal changes. Combining the data mining results with the data mining results, the daily travel model of road traffic vehicles in intelligent city is established. The results of the case study showed that the WND-LSTM model outperformed ARIMA (88.48%), LR (65.79%), SVR (70.46%), KNN (68.21%), SAEs (66.95%), GRU (68.43%), and LSTM (70.41%) in MAPE, respectively, with an average accuracy improvement of 71.25% (MAPE of 0.651%)., Competing Interests: The authors declare that they have no conflicts of interest regarding the publication of this work., (Copyright © 2022 SuYuan Ma and MingYe Zhao.)

Since the 1990s, with the continuous advancement of urbanization, the proportion of urban population has gradually increased. There is a serious shortage of land resources, and people's demand for underground space is increasing day by day. The construction of subway stations has developed into an inevitable trend in the future construction engineering industry, and it is also necessary to select the best solution from various solutions. The purpose of this paper is to study how to evaluate and analyze the economy of the deep foundation pit envelope structure of subway stations based on fuzzy logic, so as to choose the optimal and most economical plan. This paper proposes a fuzzy comprehensive evaluation method based on fuzzy logic, which is a reasonable method for the classic evaluation index. The experimental results of this paper show that in 2015 about 8% of people chose to travel by subway. By 2020, 54.5% of people chose to travel by subway, an increase of 46.5% during this period. It can be seen that more and more people are willing to take the subway, and subway transportation is a public transportation mode with large transportation volume. It has obvious public welfare, and it can relieve the urban traffic pressure very well, so the investment in subway construction in various cities is also increasing., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Puzhen An et al.)

With the advent of the information technology revolution and the Internet era, information technology is gradually occupying an important position and becoming an important strategic factor in economic development. As an emerging technology that has been developing continuously in recent years, big data is becoming an important industry to improve the innovation and development of the urban economy. Like AI technology, cloud computing, and the Internet, big data has become an important application technology for economic growth and economic efficiency improvement in today's world. It is an effective means of progress and development in a region and an important strategic resource. As a new technology, big data has attracted more and more attention from all walks of life. Many companies have turned their attention to developing big data for economic benefits. "Enjoy your old age" is the yearning of every old man and his family. In recent years, the national level has been committed to "creating an urban built environment for the elderly to achieve healthy aging." From the perspective of promoting the physical and mental health of the elderly, this paper analyzes the impact of the urban built environment on the physical and mental health of the elderly based on the needs of the elderly and puts forward countermeasures and suggestions based on the current status and existing problems of the urban built environment for the elderly. Based on the combined data analysis method and technology in big data, this paper conducted a field questionnaire survey on a total of 4,000 elderly people in urban and rural areas by means of the questionnaire survey. It is found that the existing problems of the built environment in the old cities include scattered content, one-sided understanding, and rigid design. According to the problems, the solutions of building consensus, paying attention to planning, combining urban characteristics, and the joint efforts of all sectors of society are put forward. And programming tools are used to combine formulas and analyze related data in detail. The analysis results show that the physical and mental health index of the elderly is highly correlated with factors such as changes in the consensus degree of the urban built environment, urban built environment planning, urban built environment policy support, and multiparty efforts in the urban built environment. Changes show a positive change., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Shuting Yan et al.)

City brain is a complex system, including online center, server network, and system with given algorithm. The core of the city brain is the intelligent system. After putting the urban brain into the intelligent nerve center, on the basis of not changing its original data structure, combining its own characteristics for design and then integrating into application, it can intelligently change the urban management mode. Urban planning leads the development of smart cities on a certain meaning, and smart city planning must have scientific and rational urban planning. The intelligent model is used to make urban planning form a more modern, convenient, and reasonable urban architectural planning. Some influential books on classical architectural theory are the theoretical basis of intelligent urban planning and even the trend and implementation blueprint of how smart cities will develop in the future. In this paper, four algorithms, ant colony algorithm, particle swarm optimization algorithm, genetic algorithm, and improved ant colony algorithm, are proposed to optimize the characteristics of urban architectural planning and landscape design; especially the security research of architecture and landscape characteristics is very important. The improved ant colony algorithm has the shortcoming of insufficient optimization ability in the face of complex path selection. By improving the influencing factors, a new ant colony algorithm is created. The improved ant colony algorithm achieves the best in security features, so it is advocated to use this algorithm for planning and design. The urban form in smart city aims to create a beautiful and comfortable urban environment, improve the competitiveness of cities in the rapid urbanization process, improve the living standards of the public, and shape the image of this beautiful city., Competing Interests: The authors declare that they have no conflicts of interest regarding this work., (Copyright © 2022 Nan Shao.)

The spatial layout and optimization of social facilities for sports are related to many factors such as urban economy, transportation, population, and urban planning. With the rapid development of artificial intelligence today, deep learning came into being. It also provides a lot of methods for our in-depth research on it. To solve the problem of unbalanced layout of urban social facilities for sports and the difficulty in meeting the needs of residents under the current background, this paper adopts the methods of M-P model, loss function, and activation function. Taking Hangzhou, a sports city that is about to host the Asian Games, as an example, it carried out an experiment to optimize the layout of urban public sports services. Through various tests and data, it divides the accessibility level of social facilities for sports in Hangzhou into four levels: high accessibility point (1.0-1.5), high accessibility point (0.5-1.0), the accessibility is average (0.2-0.5), and the accessibility is poor (<0.2). It also concluded that the areas with high accessibility (1.0-1.5) are Shangcheng District and Binjiang District, and the layout of sports facilities is optimal. According to the minimum facility point model, Xiaoshan District and Yuhang District need to add 6 large-scale social facilities for sports. Through this experiment, this paper can also provide a reference for other urban layouts. This has significance for the optimization of sports facilities and the optimization of public facilities., Competing Interests: The author declares that there are no conflicts of interest., (Copyright © 2022 Tieying Huang.)

At present, China is at an essential stage in the progress of social civilisation. At the same time, China's current economic level is developing rapidly and the level of urbanisation is also increasing. However, the uncontrolled development of urban space and excessive consumption of land resources have led to many urban ecological and environmental problems. As a result, there is an urgent need to improve the urban habitat. Plant landscaping is an important part of the urban environment. In addition, plant landscaping is also a crucial part of the visual arts and plays a key role in the shaping of urban spaces. In the context of the urban construction boom, people are increasingly demanding quality in the urban environment. Spatial scale, as a vital factor influencing the visual effect of planting, is gradually becoming a focus of landscape design. Urban greening based on plant landscape can not only improve the urban ecological environment and enhance people's quality of life but also resolve the contradiction between the demand for urban green space and the continuous reduction of urban greening land. Therefore, plant landscaping is recognised as a key step towards global sustainable development. However, according to current research and application practice, the development of urban greenery is limited and hindered by the value of plant landscaping and its applications. In addition, no comprehensive theoretical system has yet been established at the plant scale. In other words, there are still problems of scale in plant landscaping, such as unreasonable density, disproportion, and unclear hierarchy. Therefore, this paper begins with the definition of plant spatial scale in the city and analyses plant spatial types and scale characteristics from multiple perspectives, so as to establish an overall knowledge of plant landscaping. After that, through a study of the current situation of plant landscaping in cities, a quantitative analysis of the visual scale of plant space in urban squares is carried out to address the issues of plant scale design in this research. The focus of the analysis is on the scale of plants in relation to related elements. Furthermore, this study explores the influence of visual aesthetic scale and psychological scale on planting based on the functional scale of plant elements. Finally, the above quantitative analyses are applied to derive some relative data criteria and to summarise the design strategies for the spatial scale of planting in the city. The findings of this study can provide some guiding suggestions and references for the future construction of urban greenery, thus promoting the orderly development of plant landscaping in cities., Competing Interests: The author declares that there are no conflicts of interest., (Copyright © 2022 Lin Tian.)

The rapid advancement of information technology in today's modern society is contributing to an increase in the general degree of civilization in society. People are pleased with technological progress, but they are also becoming more aware that a major challenge confronting the advancement of social civilization at the moment is determining how to alleviate the difficulties associated with traveling and participating in social activities for the blind, as well as increasing the frequency with which they go out, travel, and participate in other activities. The blindness equipment that is now accessible in China is no longer suitable to meet the needs of blind people, but the growth of smart cities offers an opportunity to change this. Guide devices are crucial among the numerous types of equipment to assist the blind, and in order to better fulfill their various demands, we must upgrade and optimize the existing devices. The Chinese People's Daily highlights some of the key barriers to blind people's access in its 2019 article: random parking that blocks blind lanes; and "snake" and "broken" blind lanes that are not created with blind people's access in mind. In a smart city, accurate placement via smart maps helps alleviate a number of traffic-related issues for blind individuals. In this paper, we propose an intelligent guide device and interactive software to provide a more intelligent way for blind people to travel, which can effectively improve blind people's traffic conditions and make their travel easy, convenient, and safe, reflecting society's concern for blind people., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Chang Wei et al.)

In this paper, we use the panel data of 281 cities in China from 2005 to 2020 for capturing the factors driving urban inclusive growth (IG). In doing this, we employ the BP neural network algorithm combined with the DEA model to measure the urban inclusive growth efficiency (IGE). Furthermore, a nest of machine learning (ML) algorithms are introduced to explore the drivers of urban IGE, which overcomes the defects of endogeneity and multicollinearity of traditional econometric methods. We find for the overall sample that entrepreneurship and innovation contribute the most to IGE, accounting for about 35%, respectively, and they are the most critical drivers, while the heterogeneity test results reveal that the contribution of influencing factors has changed for different regions such as the eastern region, the central region, and the western region. Based on the experimental results of the ML model, we provide some policy suggestions for China and similar developing countries and emerging economies to promote IG., Competing Interests: The authors declare that they have no conflicts of interest regarding the publication of this study., (Copyright © 2022 Shuangshuang Fan and Xiaoxue Liu.)

A smart city is an intelligent space, in which large amounts of data are collected and analyzed using low-cost sensors and automatic algorithms. The application of artificial intelligence and Internet of Things (IoT) technologies in electronic health (E-health) can efficiently promote the development of sustainable and smart cities. The IoT sensors and intelligent algorithms enable the remote monitoring and analyzing of the healthcare data of patients, which reduces the medical and travel expenses in cities. Existing deep learning-based methods for healthcare sensor data classification have made great achievements. However, these methods take much time and storage space for model training and inference. They are difficult to be deployed in small devices to classify the physiological signal of patients in real time. To solve the above problems, this paper proposes a micro time series classification model called the micro neural network (MicroNN). The proposed model is micro enough to be deployed on tiny edge devices. MicroNN can be applied to long-term physiological signal monitoring based on edge computing devices. We conduct comprehensive experiments to evaluate the classification accuracy and computation complexity of MicroNN. Experiment results show that MicroNN performs better than the state-of-the-art methods. The accuracies on the two datasets (MIT-BIH-AR and INCART) are 98.4% and 98.1%, respectively. Finally, we present an application to show how MicroNN can improve the development of sustainable and smart cities., Competing Interests: No potential conflicts of interest were reported by the authors., (Copyright © 2022 Jin Wu et al.)

The temporal and spatial difference between the urban ecological environment and economic development refers to the unbalanced and insufficient contradiction between the quality of urban ecological environment and the development of economic strength. Based on the relevant theories of urban ecological environment and economic development, this paper explores the development laws of urban ecology and economic development and uses graph neural network algorithm to model the spatial and temporal dependence of the city's ecological environment in a province. The quality data and economic development strength data are analyzed in detail. The analysis results show that the ecological benefit index and economic benefit index of each city in the province have reached above 0.6 after 5 years of development. The level of coordinated urban development has improved significantly compared with 2017. However, in the process of the development of the market economy, it is necessary to rationally adjust the proportion of the secondary industry and the tertiary industry in the urban production structure and continuously promote the balanced development of the economy and ecology., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Wenbo Zhang and Binggeng Xie.)

Nowadays, the problem of road traffic safety cannot be ignored. Almost all major cities have problems such as poor traffic environment and low road efficiency. Large-scale and long-term traffic congestion occurs almost every day. Transportation has developed rapidly, and more and more advanced means of transportation have emerged. However, automobile is one of the main means of transportation for people to travel. In the world, there are serious traffic jams in almost all cities. The excessive traffic flow every day leads to the paralysis of the urban transportation system, which brings great inconvenience and impact to people's travel. Various countries have also actively taken corresponding measures, i.e., traffic diversion, number restriction, or expanding the scale of the road network, but these measures can bring little effect. Traditional intelligent traffic flow forecasting has some problems, such as low accuracy and delay. Aiming at this problem, this paper uses the model of the combination of Internet of Things and big data to apply and analyze its social benefits in intelligent traffic flow forecasting and analyzes its three-tier network architecture model, namely, perception layer, network layer, and application layer. Research and analyze the mode of combining cloud computing and edge computing. From the multiperspective linear discriminant analysis algorithm of the combination method of combining the same points and differences between data and data into multiple atomic services, intelligent traffic flow prediction based on the combination of Internet of Things and big data is performed. Through the monitoring and extraction of relevant traffic flow data, data analysis, processing and storage, and visual display, improve the accuracy and effectiveness and make it easier to improve the prediction accuracy of overall traffic flow. The traffic flow prediction of the system of Internet of Things and big data is given through the case experiment. The method proposed in this paper can be applied in intelligent transportation services and can predict the stability of transportation and traffic flow in real time so as to optimize traffic congestion, reduce manual intervention, and achieve the goal of intelligent traffic management., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Bing Liu et al.)

In the present era, people are facing enough challenges, either personally or technically, and some people do suffer from having to keep up with the current technological improvements. The Guangdong-Hong Kong-Macao Greater Bay Area (GHKMGBA) is one of the areas that has been highly managed for tourism with economic networks in it. Here, the exploitation results in underground spacing management automate the alleviation process using various methods. Apart from the characterization, it is one such mandatory consideration to create a master plan with the rise of utilization and urban underground spacing planned to be placed among large cities for tourism is considered. This paper focuses on the strategy to understand the concepts and popularisation of urban underground spacing. This matter is followed by a complementary approach with a supportive technical system. This research focuses on economic development in the cities of GHKMGBA, and the analysis is carried out with the implementation of the backpropagation neural network (BPNN)., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Yuguang Ren et al.)

Relying on the advantages of its input factors, the resource-based economy has achieved rapid development. However, with the global emphasis on scientific development, various contradictions have sharply reduced the competitiveness of the resource-based economy. In the process of a new round of changes in the world economic pattern and the adjustment of China's development strategy, most resource-based economies have begun to implement transformation actively or passively. Resource-based economy was mostly established and developed in the period of planned economy, which made great contributions to national construction and accomplished brilliant achievements in regional economic and social development. However, the development of natural resources always goes through stages of development, growth, maturity, and decline. Therefore, resource-based cities also have problems of rise, prosperity, and decline. From the perspective of adaptive space division, this paper analyzes and studies the teaching of the coordinated development of resource-based economy in the transformation of the resource-based economy and environment economy and puts forward the panel data model, logistic curve, and other algorithm models. After optimization, the collaborative development model is designed. Based on the analysis of the model, it is found that the error analysis of the model has improved by 77.3% and the average growth rate of transformation benefits is generally 56.8%., Competing Interests: The author does not have any possible conflicts of interest., (Copyright © 2022 Jiangong Yang.)

The current town ecological landscape planning and governance methods are mainly based on the high quality, high energy-saving, and environmental protection effect of the town ecological landscape. How to innovate the town ecological landscape planning and governance process with the help of Internet of things technology and fuzzy optimization method is the current development trend. Based on this, this paper studies the application of Internet of things technology in town ecological landscape planning and management. Firstly, a small town ecological landscape evaluation model based on fuzzy optimization algorithm is proposed. Combined with multivariate matrix transformation function, the authenticity data of ecological landscape are simulated. The original analysis of different types of small town ecological landscape is realized by selecting the multivariate extremum of autocorrelation function curve in the process of planning and governance. Secondly, in the simulation evaluation link, the fuzzy evaluation method is adopted and improved. At the same time, the improved three-dimensional original planning governance model is used to comprehensively analyze the simulation results of three-dimensional landscape planning governance. Finally, by designing fuzzy simulation experiments, the application effects of different Internet of things technologies in town ecological landscape planning and governance are analyzed. The experimental results show that the correlation data indicators of fuzzy optimization methods corresponding to different Internet of things technologies are very different. The application effect of different types of Internet of things technology in ecological landscape planning and governance of small towns is targeted and shows strong regularity., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Yu Ying et al.)

Neural network refers to an algorithmic mathematical model that imitates the behavioral characteristics of animal neural networks and performs distributed information processing. This kind of network depends on the complexity of the system and needs to adjust the internal node relationship, so as to achieve the purpose of processing information. With the continuous development of the economy, the transportation problem needs to be solved urgently, and the urban subway has emerged at the historic moment. The subway is a fast, large-capacity, electric-driven rail transit built in the city. The advantages of the subway provide conditions for the mitigation of urban traffic, due to the large number of cars, traffic jams, frequent accidents, and serious environmental pollution. In the city center, there are more cars and less space, and the parking lot is not commensurate with the number of cars, making parking difficult. This paper aims to study the intelligent performance evaluation of urban subway PPP projects based on deep neural network models. The subway project has a large investment, a long period, and a wide range, but the development time of the subway in China is relatively short. In order to promote the stable progress of subway projects, it is very necessary to conduct intelligent performance evaluation on subway projects. This paper compares and analyzes the basic characteristics of the PPP model and verifies the applicability and necessity of the PPP model in urban subway transportation projects. Through the investigation of relevant literature, this article puts forward the research content of the social impact assessment of subway projects. The experimental results of this paper show that, from the perspective of whether it is necessary to evaluate the performance of PPP projects, 65% of people think it is very necessary, and 22% think it is more necessary. 3% of people think it is unnecessary, and 10% of people hold an indifferent attitude. These data show that the intelligent performance evaluation of urban subway PPP projects has exploratory significance for urban infrastructure design and construction., Competing Interests: The authors declare that there are no conflicts of interest with any financial organizations regarding the material reported in this manuscript., (Copyright © 2022 Weizhi Fan et al.)

In order to improve the evaluation effect of the economic and social development pioneer area, this paper constructs the evaluation index system of the economic and social development pioneer area based on the spatial network structure analysis method and obtains an intelligent analysis system. Moreover, from the perspective of economic development information flow, this paper uses information flow direction analysis method and advantage flow analysis method to discuss the structural characteristics of urban economic development network in the economic belt, providing new methods and perspectives for the study of urban economic development flow. In addition, this paper attempts to propose a universal method for quantitative research on the "flow space" structure of urban economic development as the forward-looking content of urban economic development. According to the simulation test results, it can be seen that the evaluation index system of the economic and social development pilot area based on the analysis of the spatial network structure proposed in this paper has a good effect., Competing Interests: The author declares that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Jing Tu.)

This paper starts from the industrial structure and characteristics of the Internet of Things and compares and analyzes the development ideas of the Internet of Things industry in the market economy under different systems. We also discuss IoT business model innovations and analyze the inadequacies of current IoT business models. We use the cost-benefit analysis method to analyze, from the aspects of social benefits, economic benefits, environmental benefits, and externalities. In this paper, factor analysis and quantitative statistics are used to calculate the weight of influencing factors, and the multilevel fuzzy evaluation method is used to score the influencing factor indicators to calculate the final score result, so as to judge the applicability of the multilevel fuzzy evaluation method to judge the profit model. In order to verify whether the establishment of economic regions plays a positive role in regional economic development, a double-difference model is established. Two sets of data from the Free Trade Zone and Hainan Free Trade Zone are selected for regression analysis, and robustness tests of various methods are carried out. This paper regresses various samples of the Hainan Free Trade Zone by region and city level to explore their characteristics in different regions. From the empirical results, it can be seen that the establishment of the Hainan Free Trade Zone has indeed promoted the economic development of the region where it is located, and this result is still significant after repeated robustness tests. Judging from the regression results by region, the establishment of the Hainan Free Trade Zone has a greater role in promoting the economic development of the eastern and western regions and it has a stronger pulling effect on the western regions than in the western regions. The policy effect of establishing a free trade zone may not be significant due to too few samples and short establishment time., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Jing Yang et al.)

As one of the important components of a city, traditional buildings in different regions just reflect the differences of cities in different regions, and the analysis of the value hierarchy of its constituent elements can reveal the corresponding urban characteristics. This paper selects the representative traditional buildings in the Yangtze River Delta, the Pearl River Delta, and the Bohai Rim region as the research object, takes "perception" as the core concept, combines questionnaires, status surveys, and other methods to obtain and filter traditional architectural elements, and uses the principal components with the help of SPSS software. The analysis method calculates the filtered traditional building elements in the three regions and obtains the principal component composition and hierarchical order of them. Finally, the data results are combined with qualitative analysis to judge the different orders of the traditional building elements in the three regions and their impact on the development of their respective urban contexts., Competing Interests: The authors state that this article has no conflicts of interest., (Copyright © 2022 Tingting Niu and Ruibin Li.)

By taking the 16 cities in Anhui Province for evaluation, the main influencing factors and indicator system for integrated urban-rural development in the new era were explored, to build the BCC model, cross-efficiency model, and game cross-efficiency model of DEA. The above models were applied for empirical analysis and comparative study on the rural revitalization and urban-rural integration efficiency in Anhui Province, to summarize the conclusions efficiency and give suggestions based on the above calculations., Competing Interests: The authors declare there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Shanhui Sun et al.)

At present, data mining technology is continuously researched in science and application. With the rapid development of remote sensing satellite industry, especially the launch of remote sensing satellites with high-resolution sensors, the amount of information obtained from remote sensing images has increased dramatically, which has largely promoted the application of remote sensing data in various industries. This technique mines useable information from less complete and accurate data while ensuring low program complexity. In order to determine the impact of data mining techniques on feature extraction of graphic images, this paper explores the relevant steps in the image recognition process, especially the image preenhancement and image extraction processes. This paper develops a preliminary set of relevant data and investigates two different extraction methods based on the availability or absence of nursing information. Aiming at the advantages and disadvantages of the two house extraction methods, this work discusses how to effectively integrate remote sensing data. It uses different data sources to describe different characteristics of buildings, analyzes and extracts effective information, and finally derives building information. The research results show that, using the SVM algorithm in data mining for image feature extraction, in the verified filtering window, the accuracy can be effectively improved by about 20%. Buildings are important objects in high-resolution remote sensing images, and their feature extraction and recognition technology is of great significance in many fields such as digital city construction, urban planning, and military reconnaissance., Competing Interests: The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (Copyright © 2022 Yi Deng et al.)

With the development of competitive sports, the enthusiasm of the public to participate in sports has gradually increased. At present, almost all streets in the city have their own fitness places, which provide a lot of help for public fitness. However, the existing fitness venues are obviously insufficient, the venues are limited, relatively single, and the open-space area is insufficient, which cannot meet the needs of mass sports fitness. Based on this, this paper studies and analyzes the prediction of urban national sports fitness demand based on the ant colony algorithm. First, this paper analyzes the National Fitness Situation and the related research on demand forecasting and puts forward the use of the ant colony algorithm to realize demand forecasting. This paper expounds on the research methods and algorithms commonly used in demand forecasting. The ant colony algorithm is used to improve the fuzzy analysis. The urban national sports fitness demand is divided into six secondary indicators, and different tertiary indicators are divided under each secondary indicator. Through simulation analysis, it is confirmed that the improved algorithm proposed in this paper converges faster and finds the best path most. At the same time, the weight of the urban national sports fitness demand index is calculated., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Wei Yue and Peng Dai.)

The disposal of municipal solid waste (MSW) is based on the divide-regional operation model at present, which brings management convenience. However, due to the constraints of the division between the operating regions, there are problems such as inflexible vehicle scheduling and low efficiency. Changing this mode will put pressure on management. It is necessary to break the constraint of the region and form a fully automatic operating scheme without too much manual management. First, the initial clusters are formed by considering the distance in the initial allocation module. Secondly, through the type labeling and reallocation module, the single big data set is transformed into multiple small data sets by considering the allocated amount of garbage and the carrying capacity of garbage vehicles. Then, this work proposes the improved hierarchical agglomerative clustering (IHAC) algorithm and the garbage collecting path planning (GCPP) algorithm to realize the intelligent allocation of waste and scheduling route planning of garbage vehicles. Finally, through simulation by real example and comparative analysis, the advantages of the proposed scheme are discussed. The results show that the proposed scheme is more effective than the original scheme and other advanced methods, which can provide decision support for the scientific and intelligent collection and transportation of MSW., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Zeming Wei et al.)

With the advancement of urbanisation, the inflow of population in China's large cities has been increasing and the demand for rental housing of "new citizens" with insufficient housing affordability has become increasingly strong. Therefore, the Chinese government proposes to provide government-subsidized rental housing (GSRH) different from public rental housing. At present, the supply mode of public rental housing in China is mainly government construction and operation, which has the problems of low supply efficiency and low service level. It is critical to explore an efficient supply model in the construction of the GSRH system. Therefore, this study, starting from the three supply subjects of government, market, and society, constructs an evolutionary game model and uses agent-based modelling simulation to explore how multisubjects achieve optimal collaboration in the supply process of GSRH. The results are as follows: First, the development of a collaborative supply system includes four stages: noncooperative behaviour, collaborative exploration, collaborative game, and three-subject collaborative supply. Second, the government is the core of realising multisubject coordination. Increasing government supervision will boost market participation, while increasing government subsidies can fully mobilise the enthusiasm of social subjects but cannot continuously improve the market's enthusiasm. Third, increasing the participation ratio of social subjects will help mobilise the enthusiasm of other subjects to participate, while the excessive participation ratio of market subjects may cause an imbalance in the collaborative supply system. This study provides theoretical support for the efficient supply of GSRH., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Xiaojun Liu et al.)

With the continuous development of the social economy, the urban residential structure is also changing, and people have higher and higher requirements for the living environment. Moreover, the landscape construction of public spaces in cities is an important part of the city. It is easy to neglect the comprehensive consideration of historical development and regional culture in architectural projects. The overall lack of individuality in urban design, the lack of characteristics of adapting measures to local conditions, and the blind emphasis on architectural landscaping have led to a serious lack of regional cultural characteristics and spiritual culture in public places. Therefore, in terms of the problems of insufficient landscape construction quality and green concepts being insufficient in the construction environment of cities, an evaluation method system is established in the paper to further study the shortcomings of the scenic area architecture. What is more, relying on the personal experience of the users in the scenic spot and understanding the real needs of the public space landscape environment around the scenic spot, scientific methods and a complete system are applied to make an overall assessment of the public space in the built residential area. Besides, according to the data analysis of the simulation experiment, the advantages and disadvantages of the public space in the residential area are extracted. Combined with the current research status, the green concept design strategy of the public space landscape environment in the scenic spot is summarized. Lastly, according to the data analysis of the simulation experiment, the evaluation satisfaction of the activity atmosphere, plant configuration, and overall layout is improved by 4.2%, 3.7%, and 3.1% compared with other methods, which proves that this study has a more reasonable planning program to meet the various needs of public open space. The development of urban landscape design provides a valuable reference., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Congxiang Tian et al.)

Real-time tracking of video sports targets has been widely used in the sports industry. In order to further improve the accuracy of real-time tracking of sports targets, this paper proposes a real-time tracking method for sports targets in smart cities in the context of Internet+. This method collects data and information on the targets in the sports process, fully considers the diversity of the sports process, and performs real-time tracking and detection of the upgraded sports targets. Finally, the experimental research shows that the method in this paper can track the target accurately and quickly in real time during the movement process, and the accuracy and real-time tracking are relatively better than other tracking methods, which can be used as a powerful tool for subsequent moving target tracking., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2022 Jianping Hu and Xinjiang Ye.)

Smart city gathers heterogeneous information, which requires a unified data access and collection mechanism. In this paper, based on the computing framework of IoT put forward to satisfy urban sensing network data acquisition, transmission, and computing technology system, according to the function requirements of IoT gateway, we put forward the method of building software system and hardware system and the urban perception network middleware architecture that can meet the demand of M2M, which can realize dynamic management of cognitive resources. It also supports ubiquitous services over HTTP. This is of great significance for providing intelligent services with diversity of solvers, controllers, and computing terminals. This paper focuses on how to comprehensively apply intelligent sensing, wireless transmission, data mining, and other technologies of the Internet of Things to associate data with typical application examples such as vehicle sensing and positioning technology and urban security sensor application. These typical applications can effectively solve the practical problems in urban operation and management, meet the needs of the expansion of the concept of Internet of things in urban management and the continuous deepening of management, and improve the scientific and intelligent level of urban operation and management., Competing Interests: The authors declare that there are no conflicts of interest., (Copyright © 2022 Chunqiao Song and Xutong Wu.)