Adaptive Neuro-Fuzzy Inference System modelling for performance prediction of solar thermal energy system

Wahiba Yaïci and Evgueniy Entchev

Renewable Energy, 2016, vol. 86, issue C, 302-315

Abstract: This study investigates in details the applicability of Adaptive Neuro-Fuzzy Inference System (ANFIS) approach for predicting the performance parameters of a solar thermal energy system. Experiments were conducted on the system under a broad range of operating conditions during different Canadian seasons and weather conditions. The experimental data were used for developing the ANFIS network model. This later was then optimised and applied to predict various performance parameters of the system.

Keywords: Solar thermal energy system; Performance prediction; Adaptive Neuro-Fuzzy Inference System; Artificial neural networks; Modelling; Numerical simulation (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:86:y:2016:i:c:p:302-315

DOI: 10.1016/j.renene.2015.08.028

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