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Intelligent Early Warning of Internet Financial Risks Based on Mobile Computing

Intelligent Early Warning of Internet Financial Risks Based on Mobile Computing
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Author(s): Mu Sheng Dong (Collaborative Innovation Center for Green Development in the Wulin San, Yangtze Normal University, China)
Copyright: 2020
Volume: 11
Issue: 2
Pages: 18
Source title: International Journal of Mobile Computing and Multimedia Communications (IJMCMC)
Editor(s)-in-Chief: Agustinus Waluyo (Monash University, Australia)
DOI: 10.4018/IJMCMC.2020040104

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Abstract

In order to establish the early warning model of internet finance, K-means algorithm improved by quantum evolutionary is used in this paper to divide risk early-warning interval by combining with the given initial value and the value-at-risk measured by China's well-known internet finance company. With the characteristics of parallelism and randomness, quantization algorithm is introduced into K-means algorithm to improve the search efficiency of original algorithm on the basis of maintaining the diversity of population. The sample is conducted with optimal segmentation by using improved algorithm to obtain the accurate early-warning interval and then the risk prediction model for internet financial institutions will be established by using the advantages of GMDH predictive mining and combining with the value-at-risk measured by “Renren Loan” Company. The effectiveness of early-warning model will be illustrated by comparing the actual situation of internet financial companies with more than 40,000 data of “Renren Loan” Company from January 2017 to October 2018.

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