A Comparative Study on Deep Learning Methods for Forecasting Load in Smart Grid
Author:
Affiliation:
1. Nitte Meenakshi Institute of Technology,Department of Electrical and Electronics Engineering,Yelahanka Bengaluru,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10234680/10234728/10234682.pdf?arnumber=10234682
Reference21 articles.
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2. Multivariate k-nearest neighbor regression for time series data - A novel algorithm for forecasting UK electricity demand;al-qahtani;Neural Networks (IJCNN) the 2013 International Joint Conference on,2013
3. Using Smart Meter Data to Improve the Accuracy of Intraday Load Forecasting Considering Customer Behavior Similarities
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5. Short-Term Load Forecasting Using an LSTM Neural Network;2020 IEEE Power and Energy Conference at Illinois (PECI),2020
Cited by 1 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. Short-Term Load Forecasting via a Multi-Layer Network Based on Feature Weight Optimization;2023 IEEE International Conference on Energy Internet (ICEI);2023-10-20
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