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GLOBAL SOLAR RADIATION PREDICTION MODEL WITH RANDOM FOREST ALGORITHM

ABSTRACT
Global solar radiation estimation is crucial for regional climate assessment and crop growth. Therefore, studies on the prediction of solar radiation are emerging. With the availability of the public data on solar radiation, computerized models have been developed as well. These predictive models play significant role in determining the potentials of regions suitable for renewable energy generation required by engineering and agricultural activities. Herein a computerized model has been presented for estimating global solar radiation. The model utilizes random forest algorithm and reached predictive value of 93.9%.
KEYWORDS
PAPER SUBMITTED: 2020-06-08
PAPER REVISED: 2020-10-19
PAPER ACCEPTED: 2020-10-26
PUBLISHED ONLINE: 2021-01-24
DOI REFERENCE: https://doi.org/10.2298/TSCI200608004K
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2021, VOLUME 25, ISSUE Special issue 1, PAGES [31 - 39]
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© 2021 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence