Energy Services Demand Forecasting Combined with Feature Preferences and Bidirectional Long- and Short-Term Memory Networks

Energy Services Demand Forecasting Combined with Feature Preferences and Bidirectional Long- and Short-Term Memory Networks

Accurate and efficient demand forecasting of customer energy services is crucial for quality and risk management in grid customer service. Therefore, this paper proposes a user energy service demand prediction model based on feature selection. The methodology includes introducing a sampling algorith...

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Bibliographic Details
Main Author: KANG Feng, TAN Huochao, SU Liwei, JIAN Donglin, WANG Shuai, QIN Hao, ZHANG Yongjun
Format: Article
Language:zho
Published: Editorial Office of Journal of Shanghai Jiao Tong University 2025-07-01
Series:Shanghai Jiaotong Daxue xuebao
Subjects:
energy services
demand forecasting
class imbalance
automatic encoder
feature optimization
multi label classification
Online Access:https://xuebao.sjtu.edu.cn/article/2025/1006-2467/1006-2467-59-7-1007.shtml
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