A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM) forecasts using a GPR (Gaussian Process Regression) model

标题

A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM) forecasts using a GPR (Gaussian Process Regression) model

作者

关键词

Gaussian Process Regression, Wind speed forecasting, Empirical Wavelet Transform, Extreme Learning Machine, Support Vector Machine

出版物

ENERGY

Volume 93, Issue -, Pages 41-56

出版商

Elsevier BV

发表日期

2015-09-29

DOI

10.1016/j.energy.2015.08.045