R. Solomon, R. Marumo, and A. Garebamono (Botswana)
Artificial intelligence, modelling, simulation and neural networks.
A model of a flat plate solar collection system has been developed via data driven experimental and simulation approach. This data has been collected from a working flat plate solar collector in the field. The model presented permits a better understanding of the heat flow process and its interaction with the fluid dynamics. This can be used as a way of monitoring performance of the flat plate solar collection system. This paper reports on an experimental process carried out using back propagation learning law to model a flat-plate solar panel system. Results show that Artificial Neural Networks (ANNs) modelled the dynamics of a solar plate collector well, compared to their conventional counterparts.
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