Xai to support K-mean algorithm for analysis of real evs charging station data

This paper explores the application of explainable artificial intelligence (XAI) as a supportive tool for the K-means clustering algorithm which analyze electric vehicles (EVs) chagrining station energy data. Under the investigation the Decision Tree were used to explain the process of clustering assignment. Under the case study investigation six real EVs charging station data were used in area-related approach. The results indicated that proposed solution for arearelated approach can be implemented for real case objects and using XAI. Also the results of clustering indicated the real working condition of ECs charging station that are supportive in decision making.