{"title":"新能源汽车对城市生态环境影响的多维分析及未来趋势预测","authors":"Xuanran Tang, Tianbing Yang, Chen Zhang, Zhenglin Xiong, Ruiqi Zhu","doi":"10.54254/2755-2721/64/20241363","DOIUrl":null,"url":null,"abstract":"This study examines the development indicators of China's new energy vehicle industry using clustering and multiple regression methods. The indicators are divided into internal and external aspects: external factors, such as the degree of completeness of charging facilities, market demand, policies and regulations, and internal factors, mainly brand types and power costs. By comparing the forecasting models of its industry data, including the exponential smoothing model, grey forecasting model and Brownian forecasting model. The forecast results show that this industry in China maintains a positive development trend in the next ten years. It shows that the development prospect of electric vehicles is very bright.The population competition model is used to model the competitive situation between new energy and traditional energy vehicles, and it is concluded that new energy vehicles are replacing traditional fuel vehicles and promoting the transformation of the automotive industry to be environmentally friendly and efficient.Collect the key measures and points in time that countries have taken to target the development of this industry in China. Analysing the data on the development of the industry before and after these events, it is found that external factors, such as other countries' policies, may inhibit the industry's growth. If other countries take action to thwart this industry in China, it may temporarily break its growth or even lead to a short-term industry recession.","PeriodicalId":350976,"journal":{"name":"Applied and Computational Engineering","volume":"124 29","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-dimensional analysis of the impact of new energy vehicles on the urban ecological environment and prediction of future trends\",\"authors\":\"Xuanran Tang, Tianbing Yang, Chen Zhang, Zhenglin Xiong, Ruiqi Zhu\",\"doi\":\"10.54254/2755-2721/64/20241363\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study examines the development indicators of China's new energy vehicle industry using clustering and multiple regression methods. The indicators are divided into internal and external aspects: external factors, such as the degree of completeness of charging facilities, market demand, policies and regulations, and internal factors, mainly brand types and power costs. By comparing the forecasting models of its industry data, including the exponential smoothing model, grey forecasting model and Brownian forecasting model. The forecast results show that this industry in China maintains a positive development trend in the next ten years. It shows that the development prospect of electric vehicles is very bright.The population competition model is used to model the competitive situation between new energy and traditional energy vehicles, and it is concluded that new energy vehicles are replacing traditional fuel vehicles and promoting the transformation of the automotive industry to be environmentally friendly and efficient.Collect the key measures and points in time that countries have taken to target the development of this industry in China. Analysing the data on the development of the industry before and after these events, it is found that external factors, such as other countries' policies, may inhibit the industry's growth. If other countries take action to thwart this industry in China, it may temporarily break its growth or even lead to a short-term industry recession.\",\"PeriodicalId\":350976,\"journal\":{\"name\":\"Applied and Computational Engineering\",\"volume\":\"124 29\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied and Computational Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54254/2755-2721/64/20241363\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied and Computational Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54254/2755-2721/64/20241363","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-dimensional analysis of the impact of new energy vehicles on the urban ecological environment and prediction of future trends
This study examines the development indicators of China's new energy vehicle industry using clustering and multiple regression methods. The indicators are divided into internal and external aspects: external factors, such as the degree of completeness of charging facilities, market demand, policies and regulations, and internal factors, mainly brand types and power costs. By comparing the forecasting models of its industry data, including the exponential smoothing model, grey forecasting model and Brownian forecasting model. The forecast results show that this industry in China maintains a positive development trend in the next ten years. It shows that the development prospect of electric vehicles is very bright.The population competition model is used to model the competitive situation between new energy and traditional energy vehicles, and it is concluded that new energy vehicles are replacing traditional fuel vehicles and promoting the transformation of the automotive industry to be environmentally friendly and efficient.Collect the key measures and points in time that countries have taken to target the development of this industry in China. Analysing the data on the development of the industry before and after these events, it is found that external factors, such as other countries' policies, may inhibit the industry's growth. If other countries take action to thwart this industry in China, it may temporarily break its growth or even lead to a short-term industry recession.