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Information Journal Paper

Title

Prediction of Scour Around Cross-Vane Structures Using Generalized Structure of Group Method of Data Handling

Pages

  13-27

Abstract

 In this study, for the first time, the Scour pattern in the vicinity of Cross-Vane Structures with I, U and J shapes in bending channels is simulated by a new artificial intelligence method called the "generalized structures Group Method of Data Handling” (GSGMDH). Compared to the Group Method of Data Handling (GMDH), the GSGMDH method is more flexible and accurate in which nodes can derive inputs from non-adjacent layers. Initially, all the parameters affecting the Scour depth in the vicinity of Cross-Vane Structures are identified and then using these parameters, six different models are defined for each of the GMDH and GSGMDH methods. After that, the data are divided into two main groups: training and test. In other words, 70% of the data are used to train artificial intelligence models and the remaining 30% are utilized to test them. By analyzing the results yielded by the artificial intelligence models, the superior models are introduced. The GMDH and GSGMDH superior models estimate the Scour values in terms of all input parameters. In addition, the accuracy of the GSGMDH models is higher than the GMDH ones. For example, for the GMDH and GSGMDH superior models, the values of "variance accounted for" in the test, mode are calculated at 73. 075 and 86. 408, respectively. Also, the superior model forecasts the objective function values with acceptable accuracy. For example, the correlation coefficient (R), the scatter index (SI), and the Nash-Sutcliffe model efficiency coefficient (NSC) for the GSGMDH superior model in the training mode are approximated 0. 913, 0. 214 and 0. 800, respectively. Based to the results of the sensitivity analysis, the shape factor    of Cross-Vane Structures, the ratio of the difference between the upstream and downstream flow depths to the height of the structure   and the densimetric sthy Froude number (Fd) are introduced as the most effective input parameters. An Uncertainty analysis exhibits that the GSGMDH superior model has an underestimated performance.

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    APA: Copy

    Shahbazbigi, Ebrahim, Yosefvand, Fariborz, YAGHOUBI, BEHROUZ, SHABANLOU, SAEID, & RAJABI, AHMAD. (2021). Prediction of Scour Around Cross-Vane Structures Using Generalized Structure of Group Method of Data Handling. JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION, 11(1 ), 13-27. SID. https://sid.ir/paper/412779/en

    Vancouver: Copy

    Shahbazbigi Ebrahim, Yosefvand Fariborz, YAGHOUBI BEHROUZ, SHABANLOU SAEID, RAJABI AHMAD. Prediction of Scour Around Cross-Vane Structures Using Generalized Structure of Group Method of Data Handling. JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION[Internet]. 2021;11(1 ):13-27. Available from: https://sid.ir/paper/412779/en

    IEEE: Copy

    Ebrahim Shahbazbigi, Fariborz Yosefvand, BEHROUZ YAGHOUBI, SAEID SHABANLOU, and AHMAD RAJABI, “Prediction of Scour Around Cross-Vane Structures Using Generalized Structure of Group Method of Data Handling,” JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION, vol. 11, no. 1 , pp. 13–27, 2021, [Online]. Available: https://sid.ir/paper/412779/en

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