Construction and Application of Short-Term and Mid-Term Power System Load Forecasting Model Based on Hybrid Deep Learning
Author:
Affiliation:
1. College of Electronic Commerce, Luoyang Normal University, Luoyang, Henan, China
2. School of Information Technology, Luoyang Normal University, Luoyang, Henan, China
Funder
National Natural Science Funds of China
2022 Henan Province Key Research and Development and Promotion Projects
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10101801.pdf?arnumber=10101801
Reference26 articles.
1. Improved Dota2 lineup recommendation model based on a bidirectional LSTM
2. Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network
3. Hybrid CNN-LSTM Model for Short-Term Individual Household Load Forecasting
4. A Hybrid System Based on LSTM for Short-Term Power Load Forecasting
5. Short term power load forecasting using Deep Neural Networks
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