Journal Article10.1016/J.SOLENER.2015.03.015
A support vector machine–firefly algorithm-based model for global solar radiation prediction
Lanre Olatomiwa,Lanre Olatomiwa,Saad Mekhilef,Shahaboddin Shamshirband,Kasra Mohammadi,Dalibor Petković,Ch. Sudheer +6 more
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TL;DR: In this article, a hybrid machine learning technique for solar radiation prediction based on some meteorological data is examined, which is developed by hybridizing the Support Vector Machines (SVMs) with Firefly Algorithm (FFA) to predict the monthly mean horizontal global solar radiation using three meteorological parameters of sunshine duration (n¯), maximum temperature (Tmax), and minimum temperature(Tmin) as inputs.
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About: This article is published in Solar Energy. The article was published on 01 May 2015. The article focuses on the topics: Mean absolute percentage error.
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