Bayesian optimization based machine learning approaches for prediction of plug-in electric vehicle state-of-charge

The growing popularity of plug-in electric vehicle (PEV) around the world makes complexity in power sector. The distribution system is subjected to overload due to the random penetration of PEVs in charging depending on their level of state-of-charge (SOC). The accurate calculation and prediction of...

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Veröffentlicht in:	International journal of emerging electric power systems 2021-12, Vol.22 (6), p.753-764
Hauptverfasser:	Deb, Subhasish, Goswami, Arup Kumar, Chetri, Rahul Lamichane, Roy, Rajesh
Format:	Artikel
Sprache:	eng
Schlagworte:	gradient boosting method-Bayesian optimization (GBM-BO) plug-in electric vehicle (PEV) random forest method-Bayesian optimization (RFM-BO) state-of-charge (SOC)
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