首页|期刊导航|建筑模拟（英文版）|ResiDualNet:A novel electric vehicle charging data imputation technique to enhance load forecasting accuracy

ResiDualNet:A novel electric vehicle charging data imputation technique to enhance load forecasting accuracy

Belal Mahmud Fahim Mohammad Kaosain Akbar Manar Amayri

建筑模拟（英文版）2025，Vol.18Issue(4)：897-922,26.

建筑模拟（英文版）2025，Vol.18Issue(4)：897-922,26.DOI:10.1007/s12273-025-1236-8

ResiDualNet:A novel electric vehicle charging data imputation technique to enhance load forecasting accuracy

Belal Mahmud Fahim ¹Mohammad Kaosain Akbar ¹Manar Amayri¹

作者信息

1. Concordia Institute for Information Systems Engineering(CIISE),Concordia University,Montreal,Canada
折叠

摘要

关键词

electric vehicle/load forecasting/missing data imputation/residual Seq2Seq/SCINet

Key words

electric vehicle/load forecasting/missing data imputation/residual Seq2Seq/SCINet

引用本文复制引用

Belal Mahmud Fahim,Mohammad Kaosain Akbar,Manar Amayri..ResiDualNet:A novel electric vehicle charging data imputation technique to enhance load forecasting accuracy[J].建筑模拟（英文版）,2025,18(4):897-922,26.

基金项目

The completion of this research was made possible thanks to the Natural Sciences and Engineering Research Council of Canada(NSERC)and a start-up grant from Concordia University,Canada. （NSERC）

建筑模拟（英文版）

ISSN：1996-3599

访问量0

下载量0

段落导航