Research on Marketing Strategy of Electric Vehicle Based on Bayesian Processing and Natural Language Analysis

Abstract

The automobile industry is an important pillar of the national economy, and the new energy automobile industry is a strategic emerging industry. This paper carries on the mathematical modeling analysis of the new energy electric vehicle. First of all, using the naive Bayesian processor in natural language processing, make a judgment through theme analysis and emotion analysis, define the coefficient into the model, and finally compare target customers' satisfaction with different brands of cars. Then use DBSCAN and UMAP algorithm to divide the fluctuating data index on the sequence, analyze its linkage by establishing linkage factor to study its correlation degree, and then quantify the problem, establish abnormal coefficient, analyze the persistence of data run out for a single index, and establish an algorithm for evaluating abnormal coefficient. According to the distribution of different data indicators, the impact index of different factors on the sales of different brands of electric vehicles is determined.