Application of BP Neural Network in Early-Warning Analysis of Investment Financial Risk in Coastal Areas

Abstract

Wang, J. and Xie, S., 2020. Application of BP neural network in early-warning analysis of investment financial risk in coastal areas. In: Gong, D.; Zhang, M., and Liu, R. (eds.), Advances in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 106, pp. 259–262. Coconut Creek (Florida), ISSN 0749-0208.Financial risks in coastal areas are not only related to the current state of capital markets, but also to the positive fiscal policy effects implemented in recent years. Foreign speculative capital has not yet had a serious impact on China's monetary and financial markets. In this paper, first, the factors of financial risk in coastal areas are identified, and the corresponding evaluation index system is established with the Delphi method. Then the back-propagation neural network model is used to carry out the early-warning analysis of the major destinations of overseas mining investments. The results show that risk warnings will be moderate in Canada, Russia, and Australia in the coming years, with fewer risk warnings in Brazil, India, and South Africa. South Africa's economy is in a poor state of economic development; Brazil's real lending rate is too high. Chinese enterprises may consider investing in overseas mining in countries where the risk warning is light.