In recent years, with the continuous acceleration of urbanization and the rapid improvement of social economy, the number of private cars has increased significantly, and the traffic pressure has increased unprecedentedly. Frequent traffic accidents not only threaten people’s lives and property, but also bring inconvenience to people’s travel due to serious traffic congestion. The traditional traffic management mode has been unable to catch up with the pace of rapid improvement, so we need a traffic management mode that can better meet the needs of modern traffic management. Data in the domain of transportation has the characteristics of large volume, high dimension and complex types. Effective traffic flow prediction based on data mining technique has important research value and practical significance for alleviating traffic congestion and realizing message benefiting the people. This paper studies the trajectory clustering and driving route optimization of new energy vehicles based on fuzzy clustering algorithm. The method of this paper is fuzzy clustering. Clustering analysis is an important means of data mining. It classifies the clustered objects according to certain rules. In a certain class, all objects are similar to each other in a sense, but the objects of different classes are quite different. After research, this algorithm has achieved remarkable results and is suitable for wide application.
Research on Trajectory Clustering and Driving Route Optimization of New Energy Vehicles Based on Fuzzy Clustering Algorithm
2023-06-01
222086 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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