Introduct Risk Prediction Protection Study Based on GA-BP and K-means Clustering

Abstract

This paper mainly focuses on the risk management problems caused by frequent extreme weather events. Firstly, a grey bp neural network model is used as a heuristic optimization algorithm to construct an IWM model, which is used to decide whether insurance company provides insurance under extreme weather conditions. Secondly, based on the Comprehensive evaluation method (RSR), a DDI evaluation model was constructed to analyze the data of 100 buildings in 10 provinces in China to help developers evaluate the rationality of decisions. Finally, a PM evaluation model is constructed based on AHP and EWM-CRITIC, and K-means clustering is used to conduct comprehensive rating and grading evaluation of 30 low-insurance landmarks, and corresponding protection strategies are designed. The comprehensive application of these models provides useful suggestions and decision support for insurance company underwriting, real estate bidding, community building protection and so on.