Artificial Neural Networks Modeling of a Shallow Solar Pond
The aim of this work is to use multi-layered feed-forward back-propagation artificial neural networks and multiple linear regressions models to predict the efficiency of the shallow solar pond. For this purpose, the experimental data collection including wind speed, solar radiation, ambient air temperature, inlet temperature of fluid and mass flow rate of the heat transfer fluid was used in order to predict pond water temperature, outlet temperature of the fluid, rate of heat the heat transfer fluid and instantaneous collection efficiency of a shallow solar pond. In addition, the obtained results are presented and discussed.
KeywordsRenewable energy Solar energy Shallow solar pond Artificial neural networks Numerical simulation
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