A Deep Learning Based Hybrid Framework for Day-Ahead Electricity Price Forecasting-Reference-Cited by-同舟云学术

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A Deep Learning Based Hybrid Framework for Day-Ahead Electricity Price Forecasting

Published:2020 Issue: Volume:8 Page:143423-143436
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zhang Rongquan^ORCID,Li Gangqiang^ORCID,Ma Zhengwei^ORCID

Funder

National Natural Science Foundation of Guangdong Province

Special Innovation Project in Higher Education of Guangdong Province

Teaching Reform Project in Higher Education of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09157856.pdf?arnumber=9157856

Cited by 55 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. A hybrid framework for day-ahead electricity spot-price forecasting: A case study in China;Applied Energy;2024-11

2. Probabilistic prediction-based multi-objective optimization approach for multi-energy virtual power plant;International Journal of Electrical Power & Energy Systems;2024-10

3. Dealing with Anomalies in Day-Ahead Market Prediction Using Machine Learning Hybrid Model;Energies;2024-09-04

4. Monitoring and estimation of urban emissions with low-cost sensor networks and deep learning;Ecological Informatics;2024-09

5. Multi-market P2P trading of cooling–heating-power-hydrogen integrated energy systems: An equilibrium-heuristic online prediction optimization approach;Applied Energy;2024-08

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