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Information Journal Paper

Title

COMPARISON OF THE PERFORMANCE OF SUPPORT VECTOR MACHINE WITH OTHER INTELLIGENT TECHNIQUES TO SIMULATE RAINFALL-RUNOFF PROCESS

Pages

  92-103

Abstract

 Simulation of RAINFALL-RUNOFF process is a major step in water engineering studies and water resources management. In this study, the RAINFALL-RUNOFF process of the SIMINEHROUD monthly (1377-1390) were simulated using SUPPORT VECTOR MACHINEs (SVM) with Radial Basis kernel Function, Polynomial and linear Bayesian Network (BN) with a PC Learning Algorithm, also conventional methods such as ARTIFICIAL NEURAL NETWORKS (ANNs) and GENE EXPRESSION PROGRAMMING (GEP) were used; finally, the results were compared with each other. Correlation Coefficient (CC), Root Mean Square Error (RMSE) and Nash-Sutcliff coefficient (NS) were used to evaluate the performance of the models. The results indicate the acceptable performance of the models and GEP model shows the highest CC (CC=0.91), minimum RMSE (RMSE=1.3 m3/s) and NS=0.82 in verification stage.

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    APA: Copy

    GHORBANI, MOHAMMAD ALI, AZANI, ATEFE, & NAGHIPOOR, LEYLA. (2016). COMPARISON OF THE PERFORMANCE OF SUPPORT VECTOR MACHINE WITH OTHER INTELLIGENT TECHNIQUES TO SIMULATE RAINFALL-RUNOFF PROCESS. JOURNAL OF WATERSHED MANAGEMENT RESEARCH, 7(13), 92-103. SID. https://sid.ir/paper/230271/en

    Vancouver: Copy

    GHORBANI MOHAMMAD ALI, AZANI ATEFE, NAGHIPOOR LEYLA. COMPARISON OF THE PERFORMANCE OF SUPPORT VECTOR MACHINE WITH OTHER INTELLIGENT TECHNIQUES TO SIMULATE RAINFALL-RUNOFF PROCESS. JOURNAL OF WATERSHED MANAGEMENT RESEARCH[Internet]. 2016;7(13):92-103. Available from: https://sid.ir/paper/230271/en

    IEEE: Copy

    MOHAMMAD ALI GHORBANI, ATEFE AZANI, and LEYLA NAGHIPOOR, “COMPARISON OF THE PERFORMANCE OF SUPPORT VECTOR MACHINE WITH OTHER INTELLIGENT TECHNIQUES TO SIMULATE RAINFALL-RUNOFF PROCESS,” JOURNAL OF WATERSHED MANAGEMENT RESEARCH, vol. 7, no. 13, pp. 92–103, 2016, [Online]. Available: https://sid.ir/paper/230271/en

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