An effective deep learning neural network model for short‐term load forecasting-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

An effective deep learning neural network model for short‐term load forecasting

Published:2020-01-17 Issue:7 Volume:32 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Li Ning¹^ORCID,Wang Lu¹,Li Xinquan¹,Zhu Qing²

Affiliation:

1. State Grid Xinjiang Electric Power Co., Ltd.Institute of Electric Power Science Urumqi China

2. NARI Technology Co, Ltd Nanjing China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.5595

Reference66 articles.

1. The path of the smart grid

2. Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid

3. Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads

4. A Strategy for Short-Term Load Forecasting by Support Vector Regression Machines

5. Fuzzy Power Allocation for Opportunistic Relay in Energy Harvesting Wireless Sensor Networks

Cited by 13 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. PConvLSTM: an effective parallel ConvLSTM-based model for short-term electricity load forecasting;International Journal of Data Science and Analytics;2024-08-05

2. Enhancing peak prediction in residential load forecasting with soft dynamic time wrapping loss functions;Integrated Computer-Aided Engineering;2024-04-26

3. P-ConvLSTM: An Effective Parallel ConvLSTM-based model for Short-term Electricity Load Forecasting;2023-07-25

4. Temporal Convolution and Multi-Attention Jointly Enhanced Electricity Load Forecasting;Web Information Systems and Applications;2023

5. Short-term Load Forecasting of Multi-Energy in Integrated Energy System Based on Multivariate Phase Space Reconstruction and Support Vector Regression Mode;Electric Power Systems Research;2022-09

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