چکیده مقاله
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 1990 2021 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 6 12 1 with hyperbolic tangent stimulus function with coefficients of determination of 0 92, and root mean squares of 1 96, respectively, the best optimal models for EC quality parameters were selected
کلیدواژهها
نویسندگان
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
شیوه ارجاع
Ahmadpour, Abbas and Mirhashemi, Seyed Hassan and Panahi, Mehdi,1400,Evaluation of the accuracy multilayer perceptron neural network with sensitive analyze in estimating monthly quality of electrical conductivity parameter in Maroon Basin,12th International River Engineering Conference
ارائهشده در
مجموعه مقالات دوازدهمین سمینار بین المللی مهندسی رودخانه4 بهمن 1400 · اهواز