Electric Load Forecasting Based on a Least Squares Support Vector Machine with Fuzzy Time Series and Global Harmony Search Algorithm

Electric Load Forecasting Based on a Least Squares Support Vector Machine with Fuzzy Time Series and Global Harmony Search Algorithm

This paper proposes a new electric load forecasting model by hybridizing the fuzzy time series (FTS) and global harmony search algorithm (GHSA) with least squares support vector machines (LSSVM), namely GHSA-FTS-LSSVM model. Firstly, the fuzzy c-means clustering (FCS) algorithm is used to calculate...

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Bibliographic Details
Main Authors: Yan Hong Chen, Wei-Chiang Hong, Wen Shen, Ning Ning Huang
Format: Article
Language:English
Published: MDPI AG 2016-01-01
Series:Energies
Subjects:
electric load forecasting
least squares support vector machine (LSSVM)
global harmony search algorithm (GHSA)
fuzzy time series (FTS)
fuzzy c-means (FCM)
Online Access:http://www.mdpi.com/1996-1073/9/2/70

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http://www.mdpi.com/1996-1073/9/2/70

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