Description of Aggregate System Clustering Algorithm and Its Application in the Analysis of Automobile Fault Law

Cluster analysis is an important means of data analysis and knowledge discovery, which provides an important basis for revealing the inherent differentiation and correlation between data. This paper expounds the data characteristics, analysis significance and hierarchical model of automobile fault rules, and describes the optimization algorithm based on system cluster analysis. The algorithm is applied to classify and analyze the data information of personal driving habits and specific faults, which provides the premise and foundation for the follow-up research on the correlation between human induced factors and faults.