Rule-based Classification and Outlier Replacement for Daily Electricity Load Forecasting-Reference-Cited by-同舟云学术

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Rule-based Classification and Outlier Replacement for Daily Electricity Load Forecasting

Published:2023-12-06 Issue: Volume:5 Page:1-6
ISSN:
Container-title:2023 IEEE PES 15th Asia-Pacific Power and Energy Engineering Conference (APPEEC)
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Author:

Thu Tun Ei Thu¹,Pyae Phyo Pyae²,Jeenanunta Chawalit³

Affiliation:

1. Sirindhorn International Institute of Technology Thammasat University,School of Management Technology,Pathum Thani,Thailand

2. Eindhoven University of Technology (TU/e),Department of Electrical Engineering,the Netherlands

3. Thammasat University,School of Management Technology, Sirindhorn International Institute of Technology,Pathum Thani,Thailand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10561890/10561899/10561972.pdf?arnumber=10561972

Reference24 articles.

1. A Short-Term Load Forecasting Method Using Integrated CNN and LSTM Network

2. Advanced ML-Based Ensemble and Deep Learning Models for Short-Term Load Forecasting: Comparative Analysis Using Feature Engineering

3. Daily Load Forecasting Based on a Combination of Classification and Regression Tree and Deep Belief Network

4. Short-Term Electricity Load Forecasting with Machine Learning

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