An Innovative Metaheuristic Strategy for Solar Energy Management through a Neural Networks Framework

نویسندگان

چکیده

Proper management of solar energy as an effective renewable source is high importance toward sustainable harvesting. This paper offers a novel sophisticated method for predicting irradiance (SIr) from environmental conditions. To this end, efficient metaheuristic technique, namely electromagnetic field optimization (EFO), employed optimizing neural network. algorithm quickly mines publicly available dataset nonlinearly tuning the network parameters. suggest optimal configuration, five influential parameters EFO are optimized by extensive trial and error practice. Analyzing results showed that proposed model can learn SIr pattern predict it unseen conditions with accuracy. Furthermore, provided about 10% 16% higher accuracy compared to two benchmark optimizers, shuffled complex evolution frog leaping algorithm. Hence, EFO-supervised be promising tool early prediction in The findings research may shed light on use advanced intelligent models development.

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ژورنال

عنوان ژورنال: Energies

سال: 2021

ISSN: ['1996-1073']

DOI: https://doi.org/10.3390/en14041196