مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

58
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

0
Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

Modeling Discharge Coefficient of Radial Gates under Submerged Flow Conditions using Kernel-Based Approaches

Pages

  109-120

Abstract

 Prediction of flow discharge coefficient of gates is one of the essential issues in water engineering sciences. In recent years, various semi-empirical equations have been developed in order to predict the discharge coefficient of radial gates that the application of these formulas under submerged Flow conditions suffered from large errors. The aim of present study is to apply robust Gaussian process regression (GPR) and Support vector machine (SVM) to predict discharge coefficient of radial gates under submerged Flow conditions and compare the obtained results with well-known semi-empirical approaches. For this purpose, an extensive experimental dataset comprises 2136 data points were used to feed the utilized methods. Different combinations of dimensionless parameters were prepared and the performance of aforementioned methods were assessed. The obtained results showed that GPR method with input parameters of y0-yt/w and yt/w yields a correlation coefficient (R) of 0. 983, a Nash-Sutcliffe efficiency (NSE) of 0. 967 and root mean squared error (RMSE) of 0. 027 and indicated superior performance compared with employed SVM and other semi-empirical approaches.

Cites

  • No record.

    • References

  • No record.

    • Cite

    APA: Copy

    ROUSHANGAR, K., Alirezazadeh Sadaghiyani, a., & SHAHNAZI, S.. (2021). Modeling Discharge Coefficient of Radial Gates under Submerged Flow Conditions using Kernel-Based Approaches. IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE, 15(1 ), 109-120. SID. https://sid.ir/paper/1053683/en

    Vancouver: Copy

    ROUSHANGAR K., Alirezazadeh Sadaghiyani a., SHAHNAZI S.. Modeling Discharge Coefficient of Radial Gates under Submerged Flow Conditions using Kernel-Based Approaches. IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE[Internet]. 2021;15(1 ):109-120. Available from: https://sid.ir/paper/1053683/en

    IEEE: Copy

    K. ROUSHANGAR, a. Alirezazadeh Sadaghiyani, and S. SHAHNAZI, “Modeling Discharge Coefficient of Radial Gates under Submerged Flow Conditions using Kernel-Based Approaches,” IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE, vol. 15, no. 1 , pp. 109–120, 2021, [Online]. Available: https://sid.ir/paper/1053683/en

    Related Journal Papers

  • No record.

    • Related Seminar Papers

  • No record.

    • Related Plans

  • No record.

    • Recommended Workshops






    Move to top