Artificial Intelligence and Statistical Techniques in Short-Term Load Forecasting: a Review-Reference-Cited by-同舟云学术

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Artificial Intelligence and Statistical Techniques in Short-Term Load Forecasting: a Review

Published:2021-12-31 Issue:6 Volume:14 Page:408
ISSN:2533-1701
Container-title:International Review on Modelling and Simulations (IREMOS)
language:
Short-container-title:IREMOS

Author:

Bou Nassif Ali,Soudan Bassel,Azzeh Mohammad,Attilli Imtinan,Almulla Omar

Publisher

Praise Worthy Prize

Subject

Electrical and Electronic Engineering,Mechanical Engineering,General Chemical Engineering,Modeling and Simulation

Link

https://www.praiseworthyprize.org/jsm/index.php?journal=iremos&page=article&op=viewFile&path[]=26166&path[]=pdf_435

Cited by 10 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. Enhancing intrusion detection in IIoT: optimized CNN model with multi-class SMOTE balancing;Neural Computing and Applications;2024-05-09

2. Short-term power load forecasting of a city in Henan Province using Attention based LTSM;2024 6th Asia Energy and Electrical Engineering Symposium (AEEES);2024-03-28

3. A Transformer based approach to electricity load forecasting;The Electricity Journal;2024-03

4. Bacterial Foraging Optimization Based Least Square Support Vector Machine for Short-Term Electricity Load Forecasting;2024 International Conference on Green Energy, Computing and Sustainable Technology (GECOST);2024-01-17

5. Development of Machine Learning Based Daily Peak Load Forecasting System for Winter Season in the State of Meghalaya in India;Lecture Notes in Electrical Engineering;2023-11-01

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