Survival analysis of electric vehicle charging behavior and the temporal evolution of feature effects

Abstract This study proposes a survival-based modeling framework that combines behavioral features with interpretable machine learning to understand and predict user churn in electric vehicle charging services. Using a dataset of 1,074 users and 107,531 charging sessions from Central European countr...

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Xehetasun bibliografikoak

Egile Nagusiak:	Matej Meža, Gregor Strle, Marko Meža
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Nature Portfolio 2025-10-01
Saila:	Scientific Reports
Gaiak:	Electric vehicle charging Machine learning Behavioral modeling Churn prediction Survival analysis
Sarrera elektronikoa:	https://doi.org/10.1038/s41598-025-18771-8
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