Journal of Intelligent & Fuzzy Systems - Volume 40, issue 4

Authors: Tan, Haoyang | Zhang, Qiang

Article Type: Research Article

Abstract: The heterogeneity of inflation expectations, especially the residents’ inflation expectations, has a great influence on controlling the actual inflation rate and the effective implementation of my country’s monetary policy. In the process of monetary policy formulation, the monetary authorities need to pay more attention to the heterogeneous expectations among microeconomic individuals. This paper introduces the genetic algorithm, a new artificial intelligence method, to analyze the demand for the heterogeneity of inflation expectations and explains the basic steps to use it and how to apply it to explain problems in economics. Moreover, this paper uses a genetic algorithm-based generation overlap model …to simulate the dynamic evolution of inflation heterogeneity among residents and the equilibrium selection process of price levels in a wide search space. The results of the simulation experiment show that it is of practical significance to use genetic algorithms to simulate the dynamic process of the heterogeneity of residents’ inflation expectations. Show more

Keywords: Genetic algorithm, inflation, simulation experiment, data mining, heterogeneity

DOI: 10.3233/JIFS-189487

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6481-6491, 2021

Authors: Zhang, Chengyuan | Li, Mingliang | Li, Yongqiang

Article Type: Research Article

Abstract: The regional real estate price bubble regulation policy is an external factor for the real estate industry. The effect of real estate regulation is difficult to determine, which is a typical problem of uncertain system analysis and forecasting, and the gray Bayesian network forecasting model is to solve the forecasting problem of economic system subject to external regulation. Based on machine learning and factor analysis models, this paper constructs a real estate bubble financial risk analysis model based on machine learning and factor analysis models. Moreover, starting from the real estate price bubble, which is a hot and difficult issue …of the social economy, this paper discusses the causes of the formation of real estate price bubbles and the mechanism of the formation of real estate price bubbles, looks for the importance of policy regulation of real estate price bubbles, and clarifies the functional game model of policy regulation of real estate price bubbles. In addition, this paper uses examples to study the model constructed in this paper. The results show that the model constructed in this paper has a certain effect. Show more

Keywords: Machine learning, factor analysis, real estate bubble, financial risk

DOI: 10.3233/JIFS-189488

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6493-6504, 2021

Authors: Wang, Hui | Shiwang, Huang

Article Type: Research Article

Abstract: The various parts of the traditional financial supervision and management system can no longer meet the current needs, and further improvement is urgently needed. In this paper, the low-frequency data is regarded as the missing of the high-frequency data, and the mixed frequency VAR model is adopted. In order to overcome the problems caused by too many parameters of the VAR model, this paper adopts the Bayesian estimation method based on the Minnesota prior to obtain the posterior distribution of each parameter of the VAR model. Moreover, this paper uses methods based on Kalman filtering and Kalman smoothing to obtain …the posterior distribution of latent state variables. Then, according to the posterior distribution of the VAR model parameters and the posterior distribution of the latent state variables, this paper uses the Gibbs sampling method to obtain the mixed Bayes vector autoregressive model and the estimation of the state variables. Finally, this article studies the influence of Internet finance on monetary policy with examples. The research results show that the method proposed in this article has a certain effect. Show more

Keywords: Autovector regression, internet finance, monetary policy, influence model

DOI: 10.3233/JIFS-189489

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6505-6515, 2021

Authors: Qing, Yang | Zejun, Wang

Article Type: Research Article

Abstract: After my country’s economy has entered a new normal, in terms of employment, which has led to the coexistence of the old and new contradictions in employment in our country and the coexistence of employment expansion and stabilization of employment. In this context, it is impossible to achieve full employment and completely eliminate unemployment by relying solely on economic growth. This paper improves traditional machine learning algorithms and builds an entrepreneurial policy analysis model based on improved machine learning to analyze the impact of entrepreneurial policies on employment. Moreover, this paper uses a projection pursuit comprehensive evaluation model optimized by …genetic algorithm to conduct empirical research on entrepreneurial environment conditions. In addition, this paper verifies its rationality by regression analysis of empirical results and TEA (Entrepreneurial Activity of All Employees) index, and deeply explores the inherent laws and development characteristics of entrepreneurial environmental conditions from multiple perspectives such as time series and spatial distribution. The research results show that the method proposed in this paper is effective. Show more

Keywords: Machine learning, improved algorithm, entrepreneurial policy, employment impact

DOI: 10.3233/JIFS-189490

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6517-6528, 2021

Authors: Liu, Hongping

Article Type: Research Article

Abstract: Precision marketing is faced with multiple levels of problems, such as pollution of the data environment and unscientific algorithms, which need to be sorted out urgently. Based on neural network technology, this paper constructs a neural network-based precision marketing model and focuses on data mining to study user churn prediction and user value enhancement, which are the two most important factors affecting marketing revenue. Moreover, this paper conducts an empirical test of the product strategy and market strategy adopted by big data precision marketing. According to the characteristics of the user population and the application scenarios of the product, this …paper puts the corresponding precision marketing methods in a targeted manner and analyzes the performance of the model through experimental research. The research results show that precision marketing methods based on big data information platforms need to be more detailed and more comprehensive. At the same time, precision marketing methods need to correspond to the sensitive information characteristics of target users and consider the background and current situation of actual market execution to effectively play it role. Show more

Keywords: Neural network, precision marketing, machine learning, algorithm improvement

DOI: 10.3233/JIFS-189491

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6529-6539, 2021

Authors: Cui, Hailei

Article Type: Research Article

Abstract: For the logistics transshipment center, it can combine historical data to compare performance vertically to clarify its own performance level and development trend, and clarify its own development shortcomings, and finally improve its own shortcomings to improve its performance. In order to study the performance evaluation methods of logistics enterprises, this paper builds a logistics enterprise performance evaluation system based on the non-radial and non-angle network SBM model based on machine learning algorithms. Moreover, this paper combines the idea of balanced scorecard to comprehensively analyze the operating efficiency of my country’s listed logistics companies through data envelopment analysis model, Malmquist …index model and Tobit regression model. In addition, this paper uses the network SBM model to conduct a static analysis of vertical comparison of listed logistics companies in different stages and different industries and combines the Malmquist index to dynamically analyze the operating efficiency of listed logistics companies in my country from a dynamic perspective. Finally, this paper analyzes the company’s operating efficiency with examples. The results show that the model constructed in this paper has a certain effect. Show more

Keywords: Non-radial and non-angle network, SBM model, logistics enterprise, performance evaluation

DOI: 10.3233/JIFS-189492

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6541-6553, 2021

Authors: Wang, Chong | Wei, Yuesong

Article Type: Research Article

Abstract: Convergence and spillover are the characteristics shown in the process of financial development. By verifying whether there is convergence and spillover in financial development within a certain region and between regions, the stage of financial development in the region can be more accurately judged. This paper combines the actual needs of financial analysis to construct a financial risk spillover effect model based on ARMA-GARCH and fuzzy calculation. The model uses ARMA-GARCH and fuzzy algorithm to verify the financial multiple risk factors. Moreover, in order to verify the effect of the model, this paper uses case data analysis to study the …model effect and combines mathematical statistics to process the model data. The research results show that the model constructed in this paper has a certain effect, and the ARMA-GARCH model is suitable for analysis and research on financial risk spillover effects. At the same time, when the statistical distribution is used to fit its error distribution, the fitting and prediction effect of the model is better. Show more

Keywords: Machine learning, fuzzy calculation, financial risk, spillover effect

DOI: 10.3233/JIFS-189493

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6555-6566, 2021

Authors: Zhao, Zengming | Chen, Wenting

Article Type: Research Article

Abstract: Monetary policy is an important means for a country to regulate macroeconomic operations and achieve established economic goals. Moreover, a reasonable monetary policy improves the efficiency of financial operations on a global scale and effectively resolves the financial crisis. At present, scholars from various countries have begun to pay attention to the issue of differentiated formulation of monetary policy among regions. This paper combines machine learning to construct a monetary policy differentiation effect analysis model based on the GVAR model. Moreover, this paper uses the gray correlation analysis method to obtain the gray correlation matrix between industries, and then introduces …the industry’s own characteristics, industry relevance and macroeconomic factors into the macro stress test of credit risk. In addition, this paper constructs a conduction model based on the industry GVAR model, and uses the first-order difference sequence of GDP growth rate, CPI growth rate and M2 growth rate of each economic region to construct a GVAR model to test the impulse response function. The results of the test show that the monetary policy shocks of various economic regions are significantly different. All in all, the research results show that the performance of the model constructed in this paper is good. Show more

Keywords: GVAR, monetary policy, regional effects, machine learning

DOI: 10.3233/JIFS-189494

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6567-6579, 2021

Authors: Lin, Nan

Article Type: Research Article

Abstract: Our country’s economic growth is overly dependent on government investment, and bank credit and money supply lack a strict monitoring mechanism. Therefore, rapid economic growth is always accompanied by inflation risks. In order to study the effect of inflation impact analysis, based on machine learning algorithms, this paper combines artificial intelligence technology to analyze the impact of inflation expectations, and constructs the central bank information disclosure index and inflation expectations index. Moreover, this paper will perform ADF unit root test on the data. In addition, after confirming that the data is stable, this paper uses the Markov Regime Transfer Vector …Autoregressive (MSVAR) model and state-dependent impulse response function to test and analyze the effect of China’s central bank communication in guiding the formation of inflation expectations. Through research, we can see that the machine learning algorithm constructed in this paper has significant effects, which can provide a reference for the analysis of the impact of inflation expectations. Show more

Keywords: Machine learning, intelligent model, inflation, improved algorithm

DOI: 10.3233/JIFS-189495

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6581-6592, 2021

Authors: Wang, Yan | Wang, Xueshun | Zhang, Wenziyi | Zheng, Ke | Fu, Xinhong

Article Type: Research Article

Abstract: Agricultural industrialization is a major reform and practice in the process of agricultural development and requires theoretical guidance. However, the current theoretical research on financial support for the development of agricultural industrialization is insufficient, which to a certain extent seriously affects the development speed of agricultural industrialization. This paper studies the nature of the part and tail probability of dependent random variable sequences with different distributions, and focuses on the random variable sequences with wide dependent structures, and obtains the relevant probability estimation formulas. At the same time, this paper also considers the application of the main results in complete …convergence. Moreover, based on the research on the nature of dependent random variable sequences, the dependent risk model is discussed, which combines Internet finance with the development of agricultural industrialization. In addition, this article uses agricultural industrialization theory and Internet finance theory to study the support of Internet finance for the development of agricultural industrialization in my country. The research results show that the model constructed in this paper has a certain effect. Show more

Keywords: Neural network, internet finance, agriculture, risk factors

DOI: 10.3233/JIFS-189496

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6593-6604, 2021