Theory-guided deep-learning for electrical load forecasting (TgDLF) via ensemble long short-term memory-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Theory-guided deep-learning for electrical load forecasting (TgDLF) via ensemble long short-term memory

Published:2021-02 Issue: Volume:1 Page:100004
ISSN:2666-7924
Container-title:Advances in Applied Energy
language:en
Short-container-title:Advances in Applied Energy

Author:

Chen Yuntian,Zhang Dongxiao^ORCID

Publisher

Elsevier BV

Reference59 articles.

1. An expert system based algorithm for short term load forecast;Rahman;IEEE Trans Power Syst,1988

2. Electric load forecasting using an artificial neural network;Park;IEEE Trans Power Syst,1991

3. Integration of new evolutionary approach with artificial neural network for solving short term load forecast problem;Singh;Appl Energy,2018

4. Demand response management with multiple utility companies: a two-level game approach;Chai;IEEE Trans Smart Grid,2014

5. A deep neural network model for short-term load forecast based on long short-term memory network and convolutional neural network;Tian;Energies,2018

Cited by 64 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reservoir evaluation using petrophysics informed machine learning: A case study;Artificial Intelligence in Geosciences;2024-12

2. Domain Knowledge-Enhanced Multi-spatial Multi-temporal PM2.5 Forecasting with Integrated Monitoring and Reanalysis Data;Environment International;2024-09

3. Spatio-Temporal Consistency Enhanced Differential Network for Interpretable Indoor Temperature Prediction;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

4. A lightweight method of integrated local load forecasting and control of edge computing in active distribution networks;iScience;2024-08

5. Intrinsically interpretable machine learning-based building energy load prediction method with high accuracy and strong interpretability;Energy and Built Environment;2024-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3