Remote monitoring system of new energy vehicles based on cluster analysis

This paper takes the driving style of new energy vehicle drivers as the research object, and uses k-means algorithm to perform cluster analysis on the data set. Through the algorithm test results of 10 neural network programs, it can be seen that the correct rate of 10 runs is more than 90.5%, and the highest correct rate is 97.6%. The experimental results show that the correctness of the BP neural network model can be well verified by the clustering analysis algorithm. The algorithm can be applied to the driver’s driving style recognition of the new energy vehicle remote monitoring system and can be used as the main algorithm for the identification of the new energy vehicle remote monitoring system in the future.