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Feature Selection Modeling on Predicting EV Charging Station Coverage Rate in Southern California

Conference paper
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Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1206)

Abstract

This project emphasizes on the meso-level dynamics behind the selection of EV charger locations. The central argument of this article is that many socio-economic and demographic factors explain the distribution of EV charging stations in Southern California. Using EV station data from the US Department of Energy and 2017 ACS data, we adopt multiple model selection method to select best demographic features in predicting the coverage rate of EV charging stations in given zip code area. In sum, we hope to provide a succinct but accurate picture that explains dispersion of EV charging stations in the Southern Californian region.

Keywords

Demographic factors Electric vehicle station allocation Simulation models 

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.Claremont Graduate UniversityClaremontUSA
  2. 2.Baylor UniversityWacoUSA

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