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Issue title: Special Section: Applied Machine Learning and Management of Volatility, Uncertainty, Complexity & Ambiguity (V.U.C.A)
Guest editors: Srikanta Patnaik
Article type: Research Article
Authors: Bin, Jianga; * | Tianli, Xiongb
Affiliations: [a] College of International Business and Economics, Jiangxi University of Finance and Economics, China | [b] School of Economics, Chongqing Technology and Business University, China
Correspondence: [*] Corresponding author Jiang Bin, College of International Business and Economics, Jiangxi University of Finance and Economics, China. E-mail: aetggfh@163.com.
Abstract: This paper analyses the significance and methods of foreign trade export forecasting. The index system of foreign trade export forecasting is determined based on the analysis of foreign trade export forecasting research results. The concepts and principles of artificial neural network and fuzzy system theory are expounded, and their respective advantages and disadvantages as well as their complementarities are analyzed. This paper introduces the types and training algorithms of evolutionary morphological neural network, combines the neural network with the fuzzy system theory, and establishes the prediction model. Finally, the evolutionary morphological neural network model is applied to the prediction of foreign trade export in view of the characteristics of export and considering the influence of various factors, the whole process of establishing evolutionary morphological neural network forecasting model is introduced in detail, and the change range of export is predicted, and the ideal forecasting results are obtained.
Keywords: Fuzzy system theory, evolutionary form, neural network, foreign trade, competitiveness analysis
DOI: 10.3233/JIFS-179944
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1701-1709, 2020
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