Applications of the Chaotic Quantum Genetic Algorithm with Support Vector Regression in Load Forecasting

Applications of the Chaotic Quantum Genetic Algorithm with Support Vector Regression in Load Forecasting

Accurate electricity forecasting is still the critical issue in many energy management fields. The applications of hybrid novel algorithms with support vector regression (SVR) models to overcome the premature convergence problem and improve forecasting accuracy levels also deserve to be widely explo...

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Bibliographic Details
Main Authors:	Cheng-Wen Lee, Bing-Yi Lin
Format:	Article
Language:	English
Published:	MDPI AG 2017-11-01
Series:	Energies
Subjects:	chaotic mapping function support vector regression (SVR) quantum genetic algorithm (QGA) electricity demand forecasting
Online Access:	https://www.mdpi.com/1996-1073/10/11/1832

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