Short-term load forecasting based on IPSO-DBiLSTM network with variational mode decomposition and attention mechanism
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-022-04174-z.pdf
Reference43 articles.
1. Fallah SN, Deo RC, Shojafar M, Conti M, Shamshirband S (2018) Computational intelligence approaches for energy load forecasting in smart energy management grids: State of the art, future challenges, and research directions. Energies 11(3):596. https://doi.org/10.3390/en11030596
2. Raza MQ, Khosravi A (2015) A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings. Renew Sust Energ Rev 50:1352–1372. https://doi.org/10.1016/j.rser.2015.04.065
3. Huang S-J, Shih K-R (2003) Short-term load forecasting via arma model identification including non-gaussian process considerations. IEEE Trans Power Syst 18(2):673–679. https://doi.org/10.1109/TPWRS.2003.811010https://doi.org/10.1109/TPWRS.2003.811010
4. M. A-HH, A. SS (2006) Fuzzy short-term electric load forecasting using kalman filter. Iee Proc Gener Transm Distrib 153(2):217–227. https://doi.org/10.1049/ip-gtd:20050088
5. Ceperic E, Ceperic V, Baric A (2013) A strategy for short-term load forecasting by support vector regression machines. IEEE Trans Power Syst 28(4):4356–4364. https://doi.org/10.1109/TPWRS.2013.2269803https://doi.org/10.1109/TPWRS.2013.2269803
Cited by 7 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. The forecasting of surface displacement for tunnel slopes utilizing the WD-IPSO-GRU model;Scientific Reports;2024-09-05
2. ELFNet: An Effective Electricity Load Forecasting Model Based on a Deep Convolutional Neural Network with a Double-Attention Mechanism;Applied Sciences;2024-07-18
3. Probabilistic load forecasting based on quantile regression parallel CNN and BiGRU networks;Applied Intelligence;2024-06-07
4. A new method of network traffic prediction based on combination model;Peer-to-Peer Networking and Applications;2024-02-08
5. Multivariate Load Forecasting Method of Integrated Energy System Based on MC-CNN-DBiLSTM Model;Environmental Science and Engineering;2024
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