{"title":"Research on New Energy Vehicle Sales Problem Based on Improved Gray Correlation and BP Neural Network","authors":"Junhao Wu, Wanyang Zuo","doi":"10.1109/ICSP54964.2022.9778827","DOIUrl":null,"url":null,"abstract":"New energy vehicles are an important development direction for the global automotive industry in the 21st century, and their sales are closely related to China's sustainable development strategy. However, compared with traditional cars, consumers still have some doubts about new energy vehicles, and their marketing needs scientific decisions. Thus, it is essential to establish a customer mining model for new energy vehicles. This paper takes three newly launched brands of new energy vehicles as research objects and establishes a customer mining model for new energy vehicles based on improved gray correlation and BP neural network with the customer satisfaction scores of each performance of the three new energy vehicles as indicators. The experimental results show that the coefficients of determination for the three models are 0.99488, 0.99317 and 0.99525,respectively, which reach the expected accuracy. This model can provide some reference and practical significance for the sales strategy of new energy vehicles.","PeriodicalId":363766,"journal":{"name":"2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSP54964.2022.9778827","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
New energy vehicles are an important development direction for the global automotive industry in the 21st century, and their sales are closely related to China's sustainable development strategy. However, compared with traditional cars, consumers still have some doubts about new energy vehicles, and their marketing needs scientific decisions. Thus, it is essential to establish a customer mining model for new energy vehicles. This paper takes three newly launched brands of new energy vehicles as research objects and establishes a customer mining model for new energy vehicles based on improved gray correlation and BP neural network with the customer satisfaction scores of each performance of the three new energy vehicles as indicators. The experimental results show that the coefficients of determination for the three models are 0.99488, 0.99317 and 0.99525,respectively, which reach the expected accuracy. This model can provide some reference and practical significance for the sales strategy of new energy vehicles.