Minimum redundancy – Maximum relevance with extreme learning machines for global solar radiation forecasting: Toward an optimized dimensionality reduction for solar time series-Reference-Cited by-同舟云学术

Minimum redundancy – Maximum relevance with extreme learning machines for global solar radiation forecasting: Toward an optimized dimensionality reduction for solar time series

Published:2017-12 Issue: Volume:158 Page:595-609
ISSN:0038-092X
Container-title:Solar Energy
language:en
Short-container-title:Solar Energy

Author:

Bouzgou Hassen^ORCID,Gueymard Christian A.

Publisher

Elsevier BV

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment

Reference59 articles.

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4. Small-scale solar radiation forecasting using ARMA and nonlinear autoregressive neural network models;Benmouiza;Theor. Appl. Climatol.,2016

5. Forecasting hourly global solar radiation using hybrid k-means and nonlinear autoregressive neural network models;Benmouiza;Energy Convers. Manage.,2013

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