Automobile Fatal Accident and Insurance Claim Analysis Through Artificial Neural Network

Xiangming Liu, G. Niu
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Abstract

This chapter presents a thorough descriptive analysis of automobile fatal accident and insurance claims data. Major components of the artificial neural network (ANN) are discussed, and parameters are investigated and carefully selected to ensure an efficient model construction. A prediction model is constructed through ANN as well as generalized linear model (GLM) for model comparison purposes. The authors conclude that ANN performs better than GLM in predicting data for automobile fatalities data but does not outperform for the insurance claims data because automobile fatalities data has a more complex data structure than the insurance claims data.
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基于人工神经网络的汽车致命事故与保险理赔分析
本章对汽车致命事故和保险索赔数据进行了全面的描述性分析。讨论了人工神经网络(ANN)的主要组成部分,并研究和仔细选择了参数,以确保有效的模型构建。利用人工神经网络和广义线性模型(GLM)构建预测模型,进行模型比较。作者得出结论,ANN在预测汽车死亡数据方面比GLM表现更好,但在预测保险索赔数据方面表现不佳,因为汽车死亡数据比保险索赔数据具有更复杂的数据结构。
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