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Issue title: Special Section: Intelligent & fuzzy theory in engineering and science
Guest editors: Teresa Guarda, Isabel Lopes and Álvaro Rocha
Article type: Research Article
Authors: Bo, Wanga; b; c; * | Tianyu, Fana | Zhiyong, Lia | Xiangtian, Niea; b; c
Affiliations: [a] School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, Henan, China | [b] Collaborative Innovation Center of Water Resources Efficient Utilization and Support Engineering, Zhengzhou, Henan, China | [c] Henan Key Laboratory of Water Environment Simulation and Treatment, Zhengzhou, Henan, China
Correspondence: [*] Corresponding author. Wang Bo, School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, Henan 450046, China. E-mail: wangbosky99@163.com.
Abstract: There is little research on the relationship between financial innovation and economic growth, and the research on the synergy between the two is basically blank. Based on this, from a general perspective, through constructing the corresponding subsystems in combination with financial innovation and economic growth, establishing the corresponding synergy model, and discovering the synergy development relationship by studying the degree of synergy in the past period, this study builds a BP neural network simulation model to predict the degree of synergy between financial innovation and economic growth in 2018 on the basis of practice. At the same time, this study compares it with the actual situation to verify its effectiveness. Through analysis, the research model has certain effectiveness, which is basically consistent with the actual development trend. The research proposes that the main trend of financial innovation from the perspective of generalized virtual economy is Internet finance. This is the first time to study this issue from a new perspective, theory and method, which expands the existing research results.
Keywords: BP neural network, financial innovation, economic growth, synergy
DOI: 10.3233/JIFS-179201
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6177-6189, 2019
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