Monthly Flow Estimation in Akarçay Basin Using Artificial Neural Network

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Six approaches for modeling monthly flows of an Akarçay basin in Turkey using Artificial Neural Network (ANN) were presented. The monthly stream flows was modeled by multi-layer perceptron type of ANN. The six approaches contain three input values as calendar month order, former year’s monthly observations and the standardized value the observations, and theirs two different usage in the network. The results were tested using the mean absolute error, traditional determination coefficient and Nash-Sutcliffe efficiency. The study demonstrates that the approach which uses the months order as input data produces reasonably satisfactory results for data of the basin. It is seen that the ANNs can be assumed as successful modeling techniques of complex and nonlinear systems. Internal structures of ANN have not been comprehended clearly but high success on the research is sound as good proof to use in monthly stream flow estimation.

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Artificial Neural Network , Monthly stream flow , Modeling , Akarcay

Afyon Kocatepe University Journal Of Science an‎d Engineering

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Afyon Kocatepe University Journal Of Science an‎d Engineering