Urban Electricity Load Forecasting Method Based on Discrepancy Compensation and Short-termSampling Contrastive Loss

Urban power load forecasting is an important content of urban smart grid planning and scheduling.However,the pro-blem of data imbalance in urban power load forecasting poses a great challenge to urban power load forecasting.Traditional single-model-based methods can hardly solve the problem of data...

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Auteur principal:	CHEN Runhuan, DAI Hua, ZHENG Guineng, LI Hui , YANG Geng
Format:	Artigo
Langue:	Chinês
Publié:	Editorial office of Computer Science 2024-04-01
Collection:	Jisuanji kexue
Sujets:	electricity load forecasting|long-short term memory networks|deep learning|contrastive learning loss
Accès en ligne:	https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2024-51-4-158.pdf
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