机译:基于家电特征分析和多任务学习的自下而期短期住宅负载预测方法
Tianjin Univ Minist Educ Key Lab Smart Grid Tianjin 300072 Peoples R China|Tianjin Univ Tianjin Key Lab Power Syst Simulat & Control Tianjin 300072 Peoples R China;
Tianjin Univ Minist Educ Key Lab Smart Grid Tianjin 300072 Peoples R China|Tianjin Univ Tianjin Key Lab Power Syst Simulat & Control Tianjin 300072 Peoples R China|State Grid Tianjin Elect Power Co Tianjin 300000 Peoples R China;
Tianjin Univ Minist Educ Key Lab Smart Grid Tianjin 300072 Peoples R China|Tianjin Univ Tianjin Key Lab Power Syst Simulat & Control Tianjin 300072 Peoples R China|State Grid Suzhou Power Supply Co Suzhou 215004 Jiangsu Peoples R China;
Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China;
State Grid Tianjin Elect Power Co Tianjin 300000 Peoples R China;
Short-term residential load forecasting; Bottom-up strategy; APPLIANCE characteristic analysis; multi-task learning; Gated recurrent unit;
机译:基于卡尔曼滤波器的自下而上方法用于家庭短期负荷预测
机译:基于卡尔曼滤波器的家庭短期负荷预测的自下而上方法
机译:基于深度学习和K均值聚类的单个住宅载荷短期预测
机译:基于CNN的袋装学习方法在智能电网中进行短期负荷预测
机译:MultiSep使用机器学习算法短期负载预测框架
机译:ADST:使用基于注意的多任务学习的深空间网络预测地铁流量
机译:基于CNN-GRU的基于CNN-GRU的混合方法,用于短期住宅负载预测
机译:住宅用具负荷特性