Using artificial neural network models and particle swarm optimization for manner prediction of a photovoltaic thermal nanofluid based collector

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• 作者：Hadi Kalani^a ; Mohammad Sardarabadi^b ; ^{m.sardarabadi@yahoo.com} ; Mohammad Passandideh-Fard^b
• 关键词：Photovoltaic thermal system ; Nanofluid ; Particle Swarm Optimization (PSO) ; Neural network
• 刊名：Applied Thermal Engineering
• 出版年：2017
• 出版时间：25 February 2017
• 年：2017
• 卷：113
• 期：Complete
• 页码：1170-1177
• 全文大小：1827 K
• 卷排序：113

文摘

In this study, different neural networks are used for modeling PVT/N systems. Experiments are performed on ZnO/water nanofluid (0.2 wt%). Particle Swarm Optimization (PSO) is used to find optimum structure of each model. Results of three models are compared and validated with the experiments. Neural networks can be well used in modeling nanofluid based solar systems.