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With the development of computer operation technology and algorithms, the lumped dynamic model is more practical, and the development and application are more comprehensive. Among them, the direct coal liquefaction residual oil pyrolysis and coking technology, as a coal-to-liquid process, can increase the oil yield of the coal liquefaction process and reduce environmental pollution. The purpose of this paper is to study the experiment and algorithm of coal direct liquefaction residual oil pyrolysis and coking technology based on lumped kinetic engineering. Starting from the lumped kinetic engineering, this paper takes the direct coal liquefaction residual oil pyrolysis and coking technology as the research object. Based on the experiment of small- and medium-sized equipment, the residual oil pyrolysis and coking experiment is carried out. This paper further analyzes the components of the experimental products and explores the factors that affect the yield of residual pyrolysis oil based on the five lumped kinetic model of coking. Experimental data shows that when the pyrolysis temperature is 450°C, the content of liquefied heavy oil HS in the pyrolysis oil is 47.87%, the content of asphaltene A is 44.28%, and the content of preasphaltene PA is 7.85%; the pyrolysis temperature is 500 °C. At this time, the content of liquefied heavy oil HS in the pyrolysis oil is 54.97%, the content of asphaltene A is 40.23%, and the content of preasphaltene PA is 4.8%. It can be seen that, with the increase of pyrolysis temperature, the content of liquefied heavy oil HS increases, and the content of asphaltene A and preasphaltene PA decreases.

In this paper, we consider a natural convection flow of an incompressible viscous fluid subject to Newtonian heating and constant mass diffusion. The proposed model has been described by the Caputo fractional operator. The used derivative is compatible with physical initial and boundaries conditions. The exact analytical solutions of the proposed model have been provided using the Laplace transform method. The obtained solutions are expressed using some special functions as the Gaussian error function, Mittag–Leffler function, Wright function, and G -function. The influences of the order of the fractional operator, parameters used in modeling the considered fluid, Nusselt number, and Sherwood number have been analyzed and discussed. The physical interpretations of the influences of the parameters of our fluid model have been presented and analyzed as well. We use the graphical representations of the exact solutions of the model to support the findings of the paper.

Game theory has become an important tool to study the competition between oligopolistic enterprises. After combing the existing literature, it is found that there is no research combining two-stage game and nonlinear dynamics to analyze the competition between enterprises for advertising. Therefore, this paper establishes a two-stage game model to discuss the effect of the degree of firms’ advertising input on their profits. And the complexity of the system is analyzed using nonlinear dynamics. This paper analyzes and studies the dynamic game for two types of application network models: data transmission model and transportation network model. Under the time-gap ALOHA protocol, the noncooperative behavior of the insiders in the dynamic data transmission stochastic game is examined as well as the cooperative behavior. In this paper, the existence of Nash equilibrium and its solution algorithm are proved in the noncooperative case, and the “subgame consistency” of the cooperative solution (Shapley value) is discussed in the cooperative case, and the cooperative solution satisfying the subgame consistency is obtained by constructing the “allocation compensation procedure.” The cooperative solution is obtained by constructing the “allocation compensation procedure” to satisfy the subgame consistency. In this paper, we propose to classify the packets transmitted by the source nodes, and by changing the strategy of the source nodes at the states with different kinds of packets, we find that the equilibrium payment of the insider increases in the noncooperative game with the addition of the “wait” strategy. In the transportation dynamic network model, the problem of passenger flow distribution and the selection of service parameters of transportation companies are also studied, and a two-stage game theoretical model is proposed to solve the equilibrium price and optimal parameters under Wardrop’s criterion.

In economic growth, the gradual increase in the effect of information technology makes the enterprise economic information management increasingly important for the survival and development of the enterprises. This paper designs an enterprise economic information management system for the complex internal economic information management business and process of enterprises. It provides daily office, information access, document preview, and transmission. The proposed design (i) copes with the inconsistency and irregularity of enterprise economic information data, (ii) quickly obtains valuable information from these massive high-frequency data, and (iii) improves the economic benefits of data assets and data management efficiency. The printing function systematizes the information management for departments such as enterprise economic information, personnel, and production. The main focus of this research includes the mode, framework, and function of the whole system software. Moreover, it also comprises of the use of Internet platform big data technology to realize the practicality, stability, and security of the system database algorithm, which has been practically used by enterprises to improve office efficiency and meet the needs of daily management of enterprises. Based on the analysis of the current status of enterprise big data application, this paper constructs an enterprise economic informational management system based on big data and also describes in detail the key technologies of enterprise economic informational data management from three aspects: NoSQL-based big data storage management, Hadoop-based economic informational big data informational and economic informational big data analysis, and mining algorithm. Provide theoretical basis and basic technical support for online decision analysis.

The rapid development of artificial intelligence brings new development opportunities and challenges to English teaching university. This paper explores the concept of “smart education” and the path of building an ecological information-based teaching model of English college by interpreting the concepts of artificial intelligence, deep learning, ecological linguistics, and language education. Artificial intelligence, especially deep learning, will be promising in many aspects, such as the analysis of individual differences of language learners, customized learning content, diversified and three-dimensional teaching media, the role of teachers as smart classroom designers, and multidimensional and dynamic formative assessments. By relying on the data mining technology of deep learning to analyze learners’ characteristics, the smart classroom design, the promotion of language learners’ independent learning, and the establishment of dynamic and complete learner profiles, the language learning process is no longer a linear process but an evolving open loop, ultimately forming a harmonious development of various ecological niches in the language learning process. In this paper, we study and design a deep learning-based English informatics teaching system to develop a deep learning-based scoring prediction model. The model incorporates deep learning models based on word embedding and text convolutional networks, which can uncover the hidden interest features of academics for English. The experimental research results prove that the online e-learning service platform cannot only effectively meet the diverse and personalized English learning needs of university students, but also improve the learning efficiency of teachers and students.

The compatibility law of prescriptions is the core link of TCM theory of “theory, method, prescription and medicine,” which is of great significance for guiding clinical practice, new drug development and revealing the scientific connotation of TCM theory, and is also one of the hot spots and difficulties of TCM modernization research. How to efficiently analyze the frequency of drug use, core combination, and association rules between drugs in prescription is a basic core problem in the study of prescription compatibility law. In this paper, a systematic study was made on the compatibility rules of traditional Chinese antiviral classical prescriptions and the mechanism of traditional Chinese medicine molecules. FP-growth algorithm was used to analyze association rules of 961 classical prescriptions collected and to explore the compatibility rules of traditional Chinese antiviral classical prescriptions. In terms of compatibility law of traditional Chinese antiviral prescriptions, this paper studied the compatibility law of traditional Chinese antiviral prescriptions based on the FP-growth algorithm and made exploratory research on the compatibility law information of 961 traditional classical antiviral prescriptions. Firstly, FP tree was constructed based on the classic recipe data set. Then, frequent item set rules were established, and association rules contained in FP tree were extracted. Finally, the frequency and association rules of antiviral TCM prescriptions were analyzed according to dosage forms (decoction, pill, paste, and ingot). The results show that the FP-growth algorithm adopted in this paper has excellent algorithm performance and strong generalization and robustness in the screening and mining of large-scale prescription data sets, which can provide important processing tools and technical methods for the study of the compatibility rule of traditional Chinese medicine prescriptions.

This paper uses the partial least squares method to construct the investor sentiment index in Chinese stock market. The Shanghai Stock Exchange 180 Index and the Shenzhen Stock Exchange 100 Index are used as samples. From the perspectives of holistic sentiment and heterogeneous sentiment, this paper studies the impact of investor sentiment on stock price crash risk. The results show that investor sentiment can significantly affect stock price crash risk in Shanghai and Shenzhen A-share markets, especially in the Shenzhen A-share market no matter from which perspective. And investor pessimism has a greater impact on stock price crash risk in the Shenzhen A-share market from the perspective of heterogeneous sentiment. Compared with the available researches, this paper makes two contributions: (i) the comparative analysis is adopted to discuss the differences between Shanghai and Shenzhen A-share markets, abandoning the research approach that takes the two markets as a whole in existing literature, and (ii) this paper not only studies the impact of investor holistic sentiment on stock price crash risk from a macro perspective, but also adds a more micro heterogeneous sentiment and conducts a comparative analysis.

In the process of global digital trade rules negotiation, game and cooperation coexist, and all parties are actively seeking cooperative relationship while negotiating game. Against this background, this paper provides a comprehensive overview of the negotiation process of global digital trade rules and analyzes the core issues of the negotiations and their implied political game. This paper firstly compares the core issues of global digital trade rules negotiations at multilateral and regional levels and quantitatively reflects the weighting relationship between core issues and keywords by means of a dynamic thematic model. In order to judge the potential partnership of each country, this paper constructs a theoretical model of partner selection for global digital trade rules negotiation from the perspective of political game and uses the data of 62 major digital trade countries for empirical testing. Compared with traditional trade agreements, the consensus reached in digital trade negotiations is less influenced by traditional economic geography factors and more influenced by the level of digital trade restrictions and political distance. When signing digital trade terms, a country tends to choose countries with similar levels of digital trade restrictions and high political similarity as partners. Financial restrictions and trade restrictions are the most important digital trade restriction factors that countries pay attention to when negotiating, and political stability is the most important political factor that countries pay attention to when negotiating. Compared with developed countries, developing countries pay more attention to market size, cultural differences, and digital infrastructure when negotiating. The formulation of global digital trade rules may follow a reconstructive path from bilateral to regional to multilateral, promoting regional digital trade rule systems at this stage and gradually expanding the scope of negotiations to the multilateral level.

All graphs under consideration are finite, simple, connected, and undirected. Adjacency matrix of a graph G is 0,1 matrix A = a i j = 0 , i f v i = v j o r d v i , v j ≥ 2 1 , i f d v i , v j = 1. . Here in this paper, we discussed new type of adjacency matrix known by 1-2 adjacency matrix defined as A 1,2 G = a i j = 0 , i f v i = v j o r d v i , v j ≥ 3 1 , i f d v i , v j = 2 , from eigenvalues of the graph, we mean eigenvalues of the 1-2 adjacency matrix. Let T n c be the set of the complement of trees of order n . In this paper, we characterized a unique graph whose least eigenvalue is minimal among all the graphs in T n c .

Based on the existing grey prediction model, this paper proposes a new grey prediction model (the fractional discrete grey model, FDGM (1, 1, t α )), introduces the modeling mechanism and characteristics of the FDGM (1, 1, t α ), and uses three groups of data to verify its effectiveness compared with that of other grey models. This paper forecasts the building energy consumption in China over the next five years based on the idea of metabolism. The results show that the FDGM (1, 1, t α ) can be transformed into other grey models through parameter setting changes, so the new model has strong adaptability. The FDGM (1, 1, t α ) is more reliable and effective than the other six compared grey models. From 2018 to 2022, the total energy consumption levels of civil buildings, urban civil buildings, and civil buildings specifically in Beijing will exhibit steady upward trends, with an average annual growth rate of 2.61%, 1.92%, and 0.78%, respectively.

The ℱ -coindex (forgotten topological coindex) for a simple connected graph G is defined as the sum of the terms ζ G 2 y + ζ G 2 x over all nonadjacent vertex pairs x , y of G , where ζ G y and ζ G x are the degrees of the vertices y and x in G , respectively. The ℱ -index of a graph is defined as the sum of cubes of the vertex degrees of the graph. This was introduced in 1972 in the same paper where the first and second Zagreb indices were introduced to study the structure dependency of total π -electron energy. Therefore, considering the importance of the ℱ -index and ℱ -coindex, in this paper, we study these indices, and we present new bounds for the ℱ -index and ℱ -coindex.

The existing Z -test for correlated proportions under classical statistics is applied when observations in the data are exact and precise. In the current paper, Z -test for correlated proportions is proposed to deal with the data having indeterminate observations. The statistic of Z -test for correlated proportions under neutrosophy is introduced in the paper. The testing procedure of the proposed test is given. The application of the proposed test is given using the price of oil data. From the application, it is clear that the proposed test outperforms the existing Z -test for correlated proportions under classical statistics in terms of flexibility, adequacy, and information. The simulation study also shows the effect of indeterminacy on the statistic of the proposed test.

The purpose of this paper is to introduce the notation of single-valued neutrosophic hyper BCK-subalgebras and a novel concept of neutro hyper BCK-algebras as a generalization and alternative of hyper BCK-algebras, that have a larger applicable field. In order to realize the article’s goals, we construct single-valued neutrosophic hyper BCK-subalgebras and neutro hyper BCK-algebras on a given nonempty set. The result of the research is the generalization of single-valued neutrosophic BCK-subalgebras and neutro BCK-algebras to single-valued neutrosophic hyper BCK-subalgebras and neutro hyper BCK-algebras, respectively. Also, some results are obtained between extended (extendable) single-valued neutrosophic BCK-subalgebras and single-valued neutrosophic hyper BCK-subalgebras via fundamental relation. The paper includes implications for the development of single-valued neutrosophic BCK-subalgebras and neutro BCK-algebras and for modelling the uncertainty problems by single-valued neutrosophic hyper BCK-subalgebras and neutro hyper BCK-algebras. The new conception of single-valued neutrosophic hyper BCK-subalgebras and neutro hyper BCK-algebras was given for the first time in this paper. We find a method that can apply these concepts in some complex networks.

GM (1, N) model is one of the grey prediction models considering the influence of many factors. This paper improves GM (1, N) model and constructs PSO-GM (1, N) model. Firstly, Lasso method is used to select the influencing factors, then the priority of influencing factors and the value of parameter N in GM (1, N) model are determined, and finally PSO method is used to optimize GM (1, N) model. Taking the vegetable supply in Henan Province as the research object, this paper makes an empirical test by using PSO-GM (1, N) model. The results show that the key factors affecting the vegetable supply in Henan Province are the number of rural employees, highway mileage, and application of pesticide. The vegetable supply in Henan Province will continue to show a steady growth trend in the next three years.

This paper determined the optimal order of FGM (1, 1) model through particle swarm optimization algorithm and combined with the World Bank business environment data to predict and analyze the business environment of economies along the Belt and Road. The empirical results show that the FGM (1, 1) model has a good predicting effect on the business environment. In terms of prediction accuracy, the FGM (1, 1) model based on particle swarm optimization algorithm to determine the optimal order is significantly better than the traditional GM (1, 1) model. The predict results show that the business environment level of economies along the Belt and Road will increase year by year from 2021 to 2022, but the overall level is still relatively low. The main innovation of this paper lies in the introduction of the fractional-order grey model into the predictive analysis of the business environment, which is of great significance to the extension and application of fractional-order models in management and economic systems.

In theory, the industrial agglomeration is a double-edged sword as there are both positive and negative externalities. China’s cities, with great disparities on degrees of the industrial agglomeration, often face different energy and carbon dioxide emission problems, which raise the question whether the industrial agglomeration promotes or inhibits energy efficiency and carbon dioxide emission. This paper explored the effects of the industrial agglomeration on carbon efficiency in China. Spatial econometric methods were implemented using panel data (2007–2016) of 285 cities above the prefecture level. The results revealed that industrial agglomerations have significant impacts on the urban carbon efficiency with significant spatial spillover effects. The agglomerations of the manufacturing and high-end productive service industries take positive effects on carbon efficiency while the low-end productive and living service industries take negative effects. As a comparison, we found that the agglomeration effects at the level of the megalopolis are greater than those at the national level, especially for the living services industry, in which the higher levels of agglomeration make the effects on carbon efficiency change from negative to positive. The divisions of labor for the central and common cities in the megalopolises are integrated into the industrial agglomeration. Furthermore, the fractional-order grey forecasting model is used in this paper. By the virtue of its advantage in dealing with small sample data which lack statistical rules, this paper makes an out-of-sample prediction of carbon efficiency and industrial agglomeration degree of Chinese cities. By adding the predicted results to the spatial correlation test, new evidence on the spatial correlation of carbon efficiency and spatial division of labor between cities is obtained. Based on the empirical results of the present study, we have proposed some policy recommendations.

Nowadays, rich quantity of information is offered on the Net which makes it hard for the clients to detect necessary information. Programmed techniques are desirable to effectively filter and search useful data from the Net. The purpose of purported text summarization is to get satisfied content handling with information variety. The main factor of document summarization is to extract benefit feature. In this paper, we extract word feature in three group called important words. Also, we extract sentence feature depending on the extracted words. With increasing knowledge on the Internet, it turns out to be an extremely time-consuming, exhausting, and boring mission to read the whole content and papers and get the relevant information on precise topics

In this paper, the fixed-time synchronization problem for a class of memristive neural networks with discontinuous neuron activation functions and mixed time-varying delays is investigated. With the help of the fixed-time stability theory, under the framework of Filippov solution and differential inclusion theory, several new and useful sufficient criteria for fixed-time synchronization are obtained by designing two types of energy-saving and simple controllers for the considered systems. Compared with the traditional fixed-time synchronization controller, the controllers used in this paper only have one power exponent term, which is a function of the system state error rather than a constant. Moreover, some previous relevant works are especially improved. Finally, two numerical examples are given to show the correctness and the effectiveness of the obtained theoretical results.

The main work of this paper focuses on identifying the heat flux in inverse problem of two-dimensional nonhomogeneous parabolic equation, which has wide application in the industrial field such as steel-making and continuous casting. Firstly, the existence of the weak solution of the inverse problem is discussed. With the help of forward solution and dual equation, this paper proves the Lipchitz continuity of the cost function and derives the Lipchitz constant. Furthermore, in order to accelerate the convergence rate and reduce the running time, this paper presents a sufficient descent Levenberg–Marquard algorithm with adaptive parameter (SD-LMAP) to solve this inverse problem. At last, compared with other methods, the results of simulation experiment show that this algorithm can obviously reduce the running time and iterative number.

Picture fuzzy set is the most widely used tool to handle the uncertainty with the account of three membership degrees, namely, positive, negative, and neutral such that their sum is bound up to 1. It is the generalization of the existing intuitionistic fuzzy and fuzzy sets. This paper studies the interval probability problems of the picture fuzzy sets and their belief structure. The belief function is a vital tool to represent the uncertain information in a more effective manner. On the other hand, the Dempster–Shafer theory (DST) is used to combine the independent sources of evidence with the low conflict. Keeping the advantages of these, in the present paper, we present the concept of the evidence theory for the picture fuzzy set environment using DST. Under this, we define the concept of interval probability distribution and discuss its properties. Finally, an illustrative example related to the decision-making process is employed to illustrate the application of the presented work.

In this paper, generalized versions of Hadamard and Fejér–Hadamard type fractional integral inequalities are obtained. By using generalized fractional integrals containing Mittag-Leffler functions, some well-known results for convex and harmonically convex functions are generalized. The results of this paper are connected with various published fractional integral inequalities.

The results of this paper provide two Hadamard-type inequalities for strongly s , m -convex functions via Riemann–Liouville fractional integrals and error estimations of well-known fractional Hadamard inequalities. Their special cases are given and connected with the results of some published papers.

In this paper, we introduce a Halpern algorithm and a nonconvex combination algorithm to approximate a solution of the split common fixed problem of quasi- ϕ -nonexpansive mappings in Banach space. In our algorithms, the norm of linear bounded operator does not need to be known in advance. As the application, we solve a split equilibrium problem in Banach space. Finally, some numerical examples are given to illustrate the main results in this paper and compare the computed results with other ones in the literature. Our results extend and improve some recent ones in the literature.

This paper concerns on two types of integral boundary value problems of a nonlinear fractional differential system, i . e ., nonlocal strip integral boundary value problems and coupled integral boundary value problems. With the aid of the monotone iterative method combined with the upper and lower solutions, the existence of extremal system of solutions for the above two types of differential systems is investigated. In addition, a new comparison theorem for fractional differential system is also established, which is crucial for the proof of the main theorem of this paper. At the end, an example explaining how our studies can be used is also given.

Based on disturbance observer, this paper develops a nonsingular terminal sliding mode control method for uncertain chaotic gyroscope system. Firstly, fuzzy logic system (FLS) is used to estimate the unknown function; then disturbance observer (DOB) is constructed to estimate the mixed disturbance, which consists of the fuzzy estimation error, external disturbance, and dead-zone input error. Subsequently, by using a nonsingular terminal sliding mode function, the control method proposed in this paper can achieve the sliding mode variable approaching a small neighborhood of zero and reduce chattering phenomenon of the tracking error and controller. Finally, comparative simulation results confirm the effectiveness of the method proposed in this paper.

Based on fuzzy logic systems and prescribed performance technology, this paper investigated the stable tracking problem of a class of nonlinear systems with unknown dead-zone inputs. Firstly, the original system is transformed into an equivalent system. Then, a Nussbaum-type function is added in the predefined performance controller to estimate the unknown control direction, and the boundedness of all signals in the closed-loop system is guaranteed. In addition, tracking errors will always remain within the prescribed performance boundaries. Finally, a comparative simulation example shows the effectiveness of the method proposed in this paper.

In today's global competition environment with rapid changes in market and technology, it is more and more difficult for enterprises to fully grasp the latest knowledge and learn all the technologies by relying on their own strength. It is particularly important for enterprises to establish a network relationship of a certain intensity with other external entities (upstream and downstream enterprises, peer enterprises, scientific research institutions, government departments, financial institutions, and other organizations) for their technological learning and improvement of technological innovation performance. From different perspectives, the academic circles have confirmed that the strength of network relationship does have an impact on the technological innovation performance of enterprises. This paper will explore the measurement scale of technology learning cost, and from the basic perspective of technology learning cost, deeply explore and analyze how enterprise technology innovation performance is affected by the strength of enterprise network relationship. This paper argues that the strength of network relationship can affect the cost of technology learning and therefore the performance of technology innovation. The main contents of this study include the following. (1) Through the collation and review of the related theories of network relationship strength, technological learning cost and technological innovation performance, and the existing research results, the theoretical model of this study is established, and the theoretical assumptions of this study are put forward. (2) A presurvey is carried out first, and the data collected from the presurvey are used to test the reliability and validity of the scale of this study, and the appropriate measurement scales for the strength of network relationship, technology learning cost, and technology innovation performance are determined. (3) Adopt the method of regression analysis combined with the SME method, to verify this paper builds the theoretical model, and further clarify the network relation intensity, technology acquisition cost, and cost of technological learning all dimensions and performance of technological innovation and network strength, technological learning mechanism between cost, and performance of technological innovation.

Based on information asymmetry theory, principal-agent theory, and risk management theory, this paper analyzes the mechanism of the impact of big data on financial decision-making, analyzing four dimensions: how big data enhances the information base for forecasting, how big data improves the relevance of decision-making, how big data builds new competitive advantages, and how big data promotes dynamic decision-making. Secondly, through the analysis of specific implementation cases of enterprise big data in financial decision-making, we focus on the real problems faced in management and the effect of solving problems through big data platform. The enterprise realizing the integration of business and finance not only can better lead business expansion, but also can improve the management level within the enterprise, which is conducive to the improvement of core competitiveness. The integration of industry and finance is essentially achieved through the application of various financial management modules to the business operations of enterprises, including budget management, capital management, fixed asset management, and financial accounting. If we want to implement the whole process of financial integration, it is impossible to achieve this manually, and we must first build a powerful information system as a guarantee. Under the guidance of theories of information asymmetry, stakeholders, and management information systems, Internet finance enterprises should build their own integrated business finance system based on the demand for business finance integration in the Internet finance industry, to enhance the matching of business finance data of Internet finance enterprises, improve the efficiency of enterprise management, and realize business finance integration. Finally, through the research of this paper, we hope to provide reference for other similar enterprises to apply big data for financial decision-making. Through the application of big data, higher economic benefits are achieved in procurement management, production control, capital budget, and investment decision compared with the previous ones. It is concluded that in the era of big data, massive data can be used to serve enterprise decision-making in depth, which can break the business and financial barriers, improve the efficiency and quality of decision-making, optimize the organizational structure and personnel, and enhance the prediction and early warning capability. The application of big data tools has become the key to assisting financial decision-making and enhancing enterprise value.

The relationship between financial system and economic development is not a simple linear relationship. In some cases, the development of finance may not improve the economic development level. This paper studies the influence of the financial system on the high-quality economic development, constructs the comprehensive index of the financial system by the factor analysis method, and calculates the green total factor productivity as the index of high-quality economic development by the CRS multiplier model. Empirically, this paper takes the panel data of 30 provinces, municipalities, and autonomous regions in China from 2005 to 2018 as samples, constructs the panel threshold model, and applies the financial system, economic development level, infrastructure, and industrial structure as threshold variables to study the nonlinear relationship between the financial system and high-quality economic development. The results demonstrate that the impact of the financial system on the high-quality economy presents an inverted U-shaped relationship when the financial system and industrial structure are the threshold variables, indicating that there is an optimal interval, that is, when the financial system threshold is between 0.1355 and 0.1377 and the industrial structure threshold is between 0.1364 and 0.1408, the financial system plays a greater role in the allocation of funds and has the most obvious positive impact on high-quality economic development. Meanwhile, the impact of the financial system on the high-quality shows a marginal decreasing trend when the economic development level and infrastructure are the threshold variables; when the economic development threshold is less than 0.1409 and the basic setting threshold is less than 0.1167, the financial system has the greatest effect on promoting high-quality economic development. Based on the research results, targeted policy suggestions are put forward.

The study of accounting profitability was initiated by the famous American scholars Ball and Brown in the 1960s. In recent years, with the continuous development of market economy, the continuous improvement of the accounting legal system and accounting standards for enterprises has promoted the research on accounting profit in capital market in China. Due to the restriction of some objective conditions, there are not many valuable research results on the relationship between accounting earnings and stock price changes, and the research methods suitable for the study of accounting earnings still need to be explored and summarized. The China Securities Regulatory Commission (CSRC) has required listed companies to publish quarterly financial and accounting reports since 2002, and the condition of using the regression analysis method to study the accounting profit of listed companies is available. In this context, this paper designs a vector autoregressive model to study the correlation between stock price and accounting profit. First, combining the literature and the research results of accounting profit at home and abroad, this paper expounds the statistical analysis of accounting profit. Then, this paper analyzes the accounting profitability of listed companies in China from static and dynamic perspectives. Finally, according to the accounting profit status and profitability statistical analysis of accounting information, accounting profit and growth relationship, and accounting profit information and the relationship between stock prices, this paper is concluded. Also, this paper shows how to improve the profitability of listed companies and how can investors effectively use the accounting earnings information of listed companies for stock investment and put forward corresponding policy suggestions.

Fuzzy mathematics has been used more and more extensively and deeply in various fields since its emergence, and it has been more and more recognized. However, there is less research on fuzzy mathematics in the field of economic management. This paper attempts to introduce fuzzy theories and methods into economic management. On the premise of introducing fuzzy decision-making theories and methods, several fuzzy theories and methods that are commonly used in economic management are given. The fuzzy correlation method of economic phenomena is proposed, and the method is used to study the correlation between economic phenomena. Besides, this paper also uses fuzzy methods to analyze the relationship between economic phenomena—fuzzy relevance, and uses fuzzy two-way decision-making methods to carry out economic management and decision-making so that the decision-making results are more reasonable, scientific, and operability. In addition, this paper rationally explains the phenomena and laws existing in economic activities from a fuzzy perspective and gives models for fuzzy inference, diagnosis, and production decision-making, which have important meaning and profound theoretical value and practical value.

In this paper, we consider a class of fractional-order systems described by the Caputo derivative. The behaviors of the dynamics of this particular class of fractional-order systems will be proposed and experienced by a numerical scheme to obtain the phase portraits. Before that, we will provide the conditions under which the considered fractional-order system’s solution exists and is unique. The fractional-order impact will be analyzed, and the advantages of the fractional-order derivatives in modeling chaotic systems will be discussed. How the parameters of the model influence the considered fractional-order system will be studied using the Lyapunov exponents. The topological changes of the systems and the detection of the chaotic and hyperchaotic behaviors at the assumed initial conditions and the considered fractional-order systems will also be investigated using the Lyapunov exponents. The investigations related to the Lyapunov exponents in the context of the fractional-order derivative will be the main novelty of this paper. The stability analysis of the model’s equilibrium points has been focused in terms of the Matignon criterion.

In this paper, we study the uniqueness questions of finite order transcendental entire functions and their difference operators sharing a set consisting of two distinct entire functions of finite smaller order. Our results in this paper improve the corresponding results from Liu (2009) and Li (2012).

The concept of frame multiresolution analysis (FMRA) on local fields of positive characteristic was given by Shah in his paper, Frame Multiresolution Analysis on Local Fields published by Journal of Operators. The author has studied the concept of minimum-energy wavelet frames on these prime characteristic fields. We continued the studies based on frame multiresolution analysis and minimum-energy wavelet frames on local fields of positive characteristic. In this paper, we introduce the notion of the construction of minimum-energy wavelet frames based on FMRA on local fields of positive characteristic. We provide a constructive algorithm for the existence of the minimum-energy wavelet frame on the local field of positive characteristic. An explicit construction of the frames and bases is given. In the end, we exhibit an example to illustrate our algorithm.

This paper is devoted to a study of the concept of edge-group choosability of graphs. We say that G is edge- k -group choosable if its line graph is k -group choosable. In this paper, we study an edge-group choosability version of Vizing conjecture for planar graphs without 5-cycles and for planar graphs without noninduced 5-cycles (2010 Mathematics Subject Classification: 05C15, 05C20).

Recently, a unified integral operator has been introduced by Farid, 2020, which produces several kinds of known fractional and conformable integral operators defined in recent decades (Kwun, 2019, Remarks 6 and 7). The aim of this paper is to establish bounds of this unified integral operator by means of α,m-convex functions. The resulting inequalities provide the bounds of all associated fractional and conformable integral operators in a compact form. Also, the results of this paper hold for different kinds of convex functions connected with α,m-convex functions.

This paper presents an abstract approach of analysing population growth in the field of algebraic topology using the tools of homology theory. For a topological space X and any point vn∈X, where vn is the n-dimensional surface, the group η=X,vn is called population of the space X. The increasing sequence from vin∈X to vjn∈X for i

In this paper, the fixed-point theorem for monotone contraction mappings in the setting of a uniformly convex smooth Banach space is studied. This paper provides a version of the Banach fixed-point theorem in a complete metric space.

This paper focuses on the role of the Internet in empowering social work to intervene in ageing-in-place services for the disabled elderly in terms of time, space, and resources. Through the practical analysis of home care service providers, the advantages and characteristics of the “Internet” for ageing-in-place services for the disabled elderly are identified, as well as some of the problems that exist in the current intelligent home care service platform. This paper proposes to improve and optimize the “Internet+” by fully enhancing the technical empowerment of the Internet, improving the integration and spanning of space, and giving full play to the role of social work on the Internet. This paper proposes to improve and optimize the “Internet+” elderly home care services for the disabled, so as to solve to a certain extent the practical problems faced by the “Internet+” elderly home care services in the early stage of development. The significance of this paper is that, through the study of the “Internet+” home care services for the elderly with disabilities, the process of the services is sorted out and summarized, and suggestions and measures are put forward for its shortcomings, providing practical methods and feasible paths for future generations, which are of great significance for other social work agencies using Internet tools.

The main purpose of this paper is to study almost α -cosymplectic pseudo metric manifold satisfying certain η -parallel tensor fields. We first focus on the concept of almost α -cosymplectic pseudo metric manifold and its curvature properties. Then, we obtain some results related to the η -parallelity of h , φ h , and τ . Moreover, the deformation of almost α -Kenmotsu pseudo metric structure is given. We conclude the paper with an illustrative example of almost α -cosymplectic pseudo metric manifold.

In this paper, a binary fuzzy cluster analysis algorithm is used for an in-depth study and analysis of high-performance computational early warning in the agricultural economy. The definition of interval type-two fuzzy set and its operation are summarized. Considering the uncertain information that will be encountered in the evaluation process, this paper constructs the evaluation model of rural informatization construction performance based on interval type-two fuzzy numbers, which improves the accuracy of the evaluation results. The fuzzy clustering centres are modified according to the nature of the fuzzy clustering centre matrix, and the optimal fuzzy clustering centres and optimal fuzzy clustering division matrix with consistent order are solved. Using the level eigenvalues to find out in the abundant water period, there are 4 monitoring sections of water quality evaluation results for still clean and 5 monitoring sections of water quality evaluation results for slight pollution. In the flat-water period, there are 2 monitoring sections of the water quality evaluation results that are still clean and 7 monitoring sections of the water quality evaluation results are slightly polluted. In the dry water period, the water quality evaluation results of the 9 monitoring sections are slightly polluted. The results and the use of integrated pollutant index evaluation method results are consistent, indicating that the use of fuzzy clustering model for water quality evaluation is practical and effective. Its functional structure includes management business, innovation business, service business, production business, and operation business functions, in addition to the design of the collection and storage scheme based on Hadoop data warehouse, to achieve accurate matching of information of science and technology agricultural services in the whole agricultural industry chain. Finally, the implementation and maintenance of the cloud-based science and technology agricultural service information system are deployed, and the operational effects of its information system-related functions are demonstrated using prototype design. This paper constructs a comprehensive information system for science and technology agricultural services based on cloud technology that integrates management, innovation, service, production, and operation, which meets not only the needs of traditional science and technology agricultural service information systems, such as expert consultation and training demonstration, but also other needs spawned by the development of agricultural modernization.

Financial supervision plays an important role in the construction of market economy, but financial data has the characteristics of being nonstationary and nonlinear and low signal-to-noise ratio, so an effective financial detection method is needed. In this paper, two machine learning algorithms, decision tree and random forest, are used to detect the company's financial data. Firstly, based on the financial data of 100 sample listed companies, this paper makes an empirical study on the fraud of financial statements of listed companies by using machine learning technology. Through the empirical analysis of logistic regression, gradient lifting decision tree, and random forest model, the preliminary results are obtained, and then the random forest model is used for secondary judgment. This paper constructs an efficient, accurate, and simple comprehensive application model of machine learning. The empirical results show that the comprehensive application model constructed in this paper has an accuracy of 96.58% in judging the abnormal financial data of listed companies. The paper puts forward an accurate and practical method for capital market participants to identify the fraud of financial statements of listed companies and has certain practical significance for investors and securities research institutions to deal with the fraud of financial statements.

In this paper, by employing the Zhang neural network (ZNN) method, an effective continuous-time LU decomposition (CTLUD) model is firstly proposed, analyzed, and investigated for solving the time-varying LU decomposition problem. Then, for the convenience of digital hardware realization, this paper proposes three discrete-time models by using Euler, 4-instant Zhang et al. discretization (ZeaD), and 8-instant ZeaD formulas to discretize the proposed CTLUD model, respectively. Furthermore, the proposed models are used to perform the LU decomposition of three time-varying matrices with different dimensions. Results indicate that the proposed models are effective for solving the time-varying LU decomposition problem, and the 8-instant ZeaD LU decomposition model has the highest precision among the three discrete-time models.

This paper adopts the intelligent scheduling method to conduct an in-depth study and analysis on the optimization of financial asset liquidity management model, elaborates and analyzes the liquidity risk management theory of commercial banks, and reviews the progress of liquidity risk management research in domestic and foreign academia as the theoretical basis of this paper. After that, we analyze the liquidity risk management of Anhui Tianchang Rural Commercial Bank from both qualitative and quantitative levels and further review and analyze the problems and causes. Finally, the full research is summarized and reviewed, theoretical and practical insights are discussed and analyzed, and future liquidity risk management research priorities and directions are elaborated. Based on the analysis results, the problems of the bank in liquidity risk management are described one by one, and further deep-seated cause discovery is carried out to summarize the problems of liquidity risk management which exist in the bank’s operation process due to the lack of liquidity risk management, unbalanced asset, and liability allocation, as well as weak emergency management capability, insufficient day-to-day liquidity monitoring, and lack of professional talents. For the problems and causes of the study, effective suggestions on how to strengthen the bank’s liquidity risk management in multiple aspects are proposed. It is hoped that, by improving the bank’s liquidity risk management and reducing the chance of liquidity risk occurrence, the bank’s sustainable development can be enhanced, and it is also hoped that it can provide some reference for the liquidity risk management of similar rural small- and medium-sized financial institutions.

The excessive vertical vibration of structures induced by walking pedestrians has attracted considerable attention in the past decades. The bipedal walking models proposed previously, however, merely focus on the effects generated by legs and ignore the effects of the dynamics of body parts on pedestrian-structure interactions. The contribution of this paper is proposing a novel pedestrian-structure interaction system by introducing the concept of the continuum and a different variable stiffness strategy. The dynamic model of pedestrian-structure coupling system is established using the Lagrange method. The classical mode superposition method is utilized to calculate the response of the structure. The state-space method is employed to determine natural frequencies and damping ratio of the coupled system. Based on the proposed model, numerical simulations and parametric analysis are conducted. Numerical simulations have shown that the continuum enables the pedestrian-structure system to achieve the stable state more efficiently than the classic model does, which idealizes the body as a concentrated or lumped mass. The parametric study reveals that the presence of pedestrians is proved to significantly decrease the frequency of human-structure interaction system and improve its damping ratio. Moreover, the parameters of the bipedal model have a noticeable influence on the dynamic properties and response of the pedestrian-structure system. The bipedal walking model proposed in this paper depicts a pattern of pedestrian-structure interactions with different parameter settings and has a great potential for a wide range of practical applications.

The maintenance of a production line is becoming more important with the development of demanding higher operational efficiency and safety in industrial system. However, a production line often operates under dynamically operational and environmental conditions and the production scheduling is also a very important factor for the maintenance of a production line. First, this paper proposes an integrated data-driven model that coordinates maintenance planning decisions with production scheduling decisions to solve the problem of scheduling and maintenance planning for a parallel-series production line. The degradation information is considered, and the total cost is to be minimized in the proposed model. Also, the total cost is related with production process and maintenance considering reliability of equipment. Then, in order to better describe the relationship between production and maintenance, the accumulative processing time of equipment is used as the input of its failure function. Also, an ability factor is developed to control its reduced level by adopting preventive maintenance. Finally, a case study is used to demonstrate the implementation and potential applications of the proposed model. The long-term wear test experiments are conducted at a research laboratory facility of Shanghai Pangyuan Machinery Co., Ltd. The result proves that the proposed method is feasible and efficient to solve the joint decision-making problem for a parallel-series production line with multivariety and small batch production. The proposed model in this paper is suitable for semiconductor manufacturing.

In this paper, an integral sliding mode controller is proposed to realize the synchroniza-tion of a class of finance chaotic systems. First, an integral sliding surface with tanh function is designed. Then, fuzzy logic systems are used to estimate unknown functions, and then based on the Lyapunov stability theorem, the proposed control method can quickly drive the synchroniza-tion error into a small neighborhood of zero, and the range of this neighborhood can be estimated. The simulation results verify that the proposed method in this paper is better than the traditional method.

Classical choice theory assumes that a decision-maker considers all feasible alternatives. However, a decision-maker in the real world can not consider all alternatives because of limited attention. In this paper, we propose a satisficing choice model to describe the choice procedure based on the incomplete preferences under the limited attention of the decision-maker. Moreover, the existence and rationality properties of the satisficing choice model on the different domains are studied combined with some proposed rationality conditions. Further, the proposed satisficing choice model is applied to a case of quality competition. Results show that the satisficing choice model of this paper is of a certain theoretical guiding significance to a kind of emergency decisions made by decision-makers under the circumstance of time pressure and limited information. It can also be the theoretical foundation for the study on the boundedly rational decision-making.

Investment portfolio can provide investors with a more robust financial management plan, but the uncertainty of its parameters is a key factor affecting performance. This paper conducts research on investment portfolios and constructs a two-stage mixed integer programming (TS-MIP) model, which comprehensively considers the five dimensions of profit, diversity, skewness, information entropy, and conditional value at risk. But the deterministic TS-MIP model cannot cope with the uncertainty. Therefore, this paper constructs a two-stage robust optimization (TS-RO) model by introducing robust optimization theory. In case experiments, data crawler technology is used to obtain actual data from real websites, and a variety of methods are used to verify the effectiveness of the proposed model in dealing with uncertainty. The comparison of models found that, compared with the traditional equal weight model, the investment benefits of the TS-MIP model and the TS-RO model proposed have been improved. Among them, the Sharpe ratio, Sortino ratio, and Treynor ratio have the largest increase of 19.30%, 8.25%, and 7.34%, respectively.

The number of conjugate classes of derangements of order $n$ is the same as the number $h(n)$ of the restricted partitions with every portion greater than $1$. It is also equal to the number of isotopy classes of $2\times n$ Latin rectangles. Sometimes the exact value is necessary, while sometimes we need the approximation value. In this paper, a recursion formula of $h(n)$ will be obtained, also will some elementary approximation formulae with high accuracy for $h(n)$ be presented. Although we may obtain the value of $h(n)$ in some computer algebra system, it is still meaningful to find an efficient way to calculate the approximate value, especially in engineering, since most people are familiar with neither programming nor CAS software. This paper is mainly for the readers who need a simple and practical formula to obtain the approximate value (without writing a program) with more accuracy, such as to compute the value in an pocket science calculator without programming function. Some methods used here can also be applied to find the fitting functions for some types of data obtained in experiments., Comment: 19 pages, 25 figures, 15 tables