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...
I tiakina i:
| Ngā kaituhi matua: | , , |
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| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
Nature Portfolio
2025-10-01
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| Rangatū: | Scientific Reports |
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1038/s41598-025-18771-8 |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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