Automobile Fatal Accident and Insurance Claim Analysis Through Artificial Neural Network

Xiangming Liu, G. Niu
{"title":"Automobile Fatal Accident and Insurance Claim Analysis Through Artificial Neural Network","authors":"Xiangming Liu, G. Niu","doi":"10.4018/978-1-7998-8455-2.ch009","DOIUrl":null,"url":null,"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.","PeriodicalId":250689,"journal":{"name":"Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-7998-8455-2.ch009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

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.
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信