@Article{jbd.2024.057612,
AUTHOR = {Annan Yang, Jiawei Zhang, Haojie Yang, Keyi Tao, Mengna Xu, Yuyu Zhao},
TITLE = {Optimization of Electric Vehicle Charging Station Layout Based on Point of Interest Data and Location Entropy Evaluation},
JOURNAL = {Journal on Big Data},
VOLUME = {6},
YEAR = {2024},
NUMBER = {1},
PAGES = {21--41},
URL = {http://www.techscience.com/jbd/v6n1/59163},
ISSN = {2579-0056},
ABSTRACT = {This study introduces an electric vehicle charging station layout optimization method utilizing Point of Interest (POI) data, addressing traditional design limitations. It details the acquisition and visualization of POI data for Yancheng’s key locations and charging stations. Employing a hybrid K-Means and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm, the study determines areas requiring optimization through location entropy and overlap analysis. The research shows that the integrated clustering approach can efficiently guide the fair distribution of charging stations, enhancing service quality and supporting the sustainable growth of the electric vehicle sector.},
DOI = {10.32604/jbd.2024.057612}
}