Prediction and analysis of relative error in electric vehicle charging stations based on an improved ConvFormer model

In order to address the issue of metering inaccuracies in charging stations that directly affect the development of electric vehicles, a prediction method for the relative error of charging stations based on the ConvFormer model is proposed. The model combines Convolutional Neural Networks (CNN) wit...

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Autori principali:	Liwen Chen, Zhibin Liu, Qingquan Yu, Xing Jiang, Huanghui Zhang, Xin Lin
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2024-08-01
Serie:	Heliyon
Soggetti:	Artificial intelligence Time series forecasting Neural network ConvFormer Relative errorr of charging stations
Accesso online:	http://www.sciencedirect.com/science/article/pii/S2405844024118713
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