Evaluation of the accuracy multilayer perceptron neural network with sensitive analyze in estimating monthly quality of electrical conductivity parameter in Maroon Basin
Publish place: 12th International River Engineering Conference
Publish Year: 1400
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
IREC12_029
تاریخ نمایه سازی: 31 اردیبهشت 1401
Abstract:
. In the present paper, in order to predict the quality electrical conductivity parameters (Ec ) in Maroon basin located in Khuzestan province, a multilayer artificial neural network of perceptron was used. The data of ۱۹۹۰-۲۰۲۱ were used for prediction. For the input and output layer, the linear function was used and for the hidden layer, different stimulus functions were used with the propagation training algorithm. Finally, the model of artificial neural network with structure (۶-۱۲-۱) with hyperbolic tangent stimulus function with coefficients of determination of ۰.۹۲, and root mean squares of ۱.۹۶, respectively, the best optimal models for EC quality parameters were selected
Keywords:
water quality. Artificial neural network. Electrical conductivity .Maroon Basin
Authors
Abbas Ahmadpour
Dept. of Water Engineering, Faculty of Water and Soil, University of Zabol, Iran
Seyed Hassan Mirhashemi
Dept. of Water Engineering, Faculty of Water and Soil, University of Zabol, Iran
Mehdi Panahi
Dept. of Water Engineering, Faculty of Agriculture, University of Zanjan. Iran.