A Comparative Analysis of Time Series Forecasting Methods for Short-Term Electricity Demand Prediction
Author:
Affiliation:
1. KAIST Convergence Research Center for College of Daejeon,Republic of Korea
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10391854/10391860/10392314.pdf?arnumber=10392314
Reference13 articles.
1. A Study on Short-term Load Forecasting Technique and its Application;Song;Korea Power Exchange,2011
2. Development of an integrated portal for demand management based on demand forecasting;Oh;Korea Electric Power Corporation Research Institute,2015
3. Hybrid Short-Term Load Forecasting Scheme Using Random Forest and Multilayer Perceptron
4. Short-term electricity demand forecasting technology in smart grid;Moon;Communications of Korean Institute of Information Scientists and Engineers,2019
5. Comparative Analysis of Artificial Intelligent Prediction Models for Nationwide Short-Term Electricity Demand
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