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A new approach based on artificial neural network (ANN) was developed in this study to determine the performance of solar collectors. The experiments were performed under the meteorological conditions of Beijing. Performance parameters obtained from the experimentation were used as training data. The backpropagation learning algorithm and logistic sigmoid transfer function were used in the ANN. Ambient...
This paper described an application of artificial neural networks (ANNs) to predict the indoor air quality (IAQ). Six indoor air pollutants and three indoor comfort variables were used as input variables to the networks. An occupant symptom metric (PIAQ) was used as the measure of indoor air quality, and employed as the output variable.Pollutant concentration, comfort variable, and PIAQ data were...
This paper describes an application of artificial neural networks (ANNs) to predict the performance of a ground-water heat pump system (GWHP). In order to gather data for training and testing the proposed ANN model, an experimental GWHP system was operated at steady state conditions. Utilizing some experimental data for training, an ANN model based on a multi-layered perception/back propagation was...
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