标题：Evaluation of Artificial Neural Networks for Electrical Conductivity and Flow Rate-based Prediction of the Nitrate Nitrogen Concentration in the U-Tapao Canal, Hatyai, Thailand
出版社：Thai Society of Higher Eduction Institutes on Environment
摘要：The aim of this study was to identify suitable artificial neural network (ANN) models for the EC-based and flowrate-based prediction of the nitrate nitrogen (NO3-N) concentration in the U-Tapao canal, located in the southern part of Thailand. Two types of four layer ANNs of the feed-forward back propagation (FFBP) and cascade-forward backpropagation (CFBP) types were evaluated for this prediction. The selected inputs of the ANNs were EC and flow rate, which were collected daily from December 2014 to March 2015. Overall, the study found that the four layer FFBP with2 neurons in the input layer, 20 neurons in the first hidden layer, 30 neurons in the second hidden layer, and a single neuronin the output layer with a tan-sigmoid transfer function was the optimal model. The FFBP model produced slightly moreaccurate results than the CFBP model. Linear regression analysis was used to predict NO3-N, which was compared withthe results of the ANNs and the performance of the ANNs was better than that of the linear regression analysis. Therefore, the ANN approach proved to be suitable as an alternative to laboratory-based analysis for the prediction of NO3-N values in the U-Tapao canal.
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