Short term load forecasting based on phase space reconstruction algorithm and bi-square kernel regression model-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Short term load forecasting based on phase space reconstruction algorithm and bi-square kernel regression model

Published:2018-08 Issue: Volume:224 Page:13-33
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Fan Guo-Feng,Peng Li-Ling,Hong Wei-Chiang^ORCID

Funder

Startup Foundation for Doctors

Educational Commission of Henan Province of China

Science and Technology of Henan Province of China

Jiangsu Provincial Department of Education

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference65 articles.

1. Priority index considering temperature and date proximity for selection of similar days in knowledge-based short term load forecasting method;Karimi;Energy,2018

2. Short-term load forecasting using a two-stage sarimax model;Tarsitano;Energy,2017

3. Short-term power load probability density forecasting method using kernel-based support vector quantile regression and Copula theory;He;Appl Energy,2017

4. Short-term electricity demand forecasting using autoregressive based time varying model incorporating representative data adjustment;Vu;Appl Energy,2017

5. Short-term residential load forecasting: Impact of calendar effects and forecast granularity;Lusis;Appl Energy,2017

Cited by 158 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. New secondary decomposition ensemble support vector regression for monthly drought index forecasting;Journal of Hydrology;2024-08

2. A Hybrid Deep Learning Model to Estimate the Future Electricity Demand of Sustainable Cities;Sustainability;2024-07-30

3. Machine learning and the cross-section of cryptocurrency returns;International Review of Financial Analysis;2024-07

4. From Time-Series to Hybrid Models: Advancements in Short-Term Load Forecasting Embracing Smart Grid Paradigm;Applied Sciences;2024-05-23

5. Short time load forecasting for Urmia city using the novel CNN-LTSM deep learning structure;Electrical Engineering;2024-05-09

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