Assessment of Adaptive neural fuzzy inference systems and support vector regression in runoff estimation(A case study:Dez Basin)

Subject Areas :

Ghazaleh Ahmadian Ahmadabad ¹ , Mahmoud Zakeri Niri ² , Saber Moazami Goudarzi ³

1 - M.s. Department of Civil Engineering, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran
2 - Department of Civil Engineering, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran
3 - Department of Civil Engineering, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran

Received: 2020-07-07 Accepted : 2020-07-07 Published : 2019-08-23

Keywords: Simulation, Support vector machine, Artificial Neural Network, Dez basin, optimal model,

Abstract :

Estimation of discharge flow in basin due to impact on water resource management can have an important economic role.In this research several computationals intelligence techniques suchas:ANN,SVR and ANFIS have been used to prediction the runoff dez basin.correlation between stations was investigated and stations of kamandan,zoorabad and daretakht were eliminated due to small correlation with around stations.then due to lack of human intervention with using xlstat software were evaluated  trend of stations and were selected stations without trend.Inorder to evaluate the performance of  models were used correlation,RMSE and NSE.Results of this research showed that ANFISwith clustering approach gives better estimation than grid partitioning approach.ANN, ANFIS and SVR have agood ability to simulate the flow of dez basin.