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Novel Method for Measuring the Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters Based on Artificial Neural Networks and Support Vector Machine
2015
Energies
The determinations of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, the direct determination requires complex detection devices and a series of standard experiments, which also wastes too much time and manpower. To address this problem, we propose machine learning models including artificial neural networks (ANNs) and support vector machines (SVM) to predict the heat collection rate and
doi:10.3390/en8088814
fatcat:rriahgsll5g6tajqscdmj4ap4e