Information Mining of New Energy Vehicles Based on Time Series Analysis in the Context of Big Data

Abstract

Based on the time series analysis data mining method, the paper explores the usage scenarios of new energy vehicles, accurately locates the timing distribution range of new energy vehicles. Firstly, the mysql database is used to preprocess the data of 1245 new energy vehicles in Beijing. Secondly, the dynamic regularization algorithm DTW is selected to cluster the preprocessed data. Then, using python software to analyze the state sequence of new energy vehicles, the results show that there are six kinds of car scenes for new energy vehicles, including: commuting to and from work, picking up and dropping off children to school, nightlife, short-distance self-driving tour, visiting relatives and friends and painters traveling. Introduction