Abstract In this article, the accuracy of a soft computing technique is evaluated in terms of discharge coefficient prediction of an improved triangular side weir. The process includes simulating the discharge coefficient with the Adaptive Neuro-Fuzzy Inference System (ANFIS). Matlab software is used for ANFIS modeling. To identify the most appropriate input variables, eight different input combinations with various numbers of inputs are examined. The performance of the proposed system is confirmed by comparing the ANFIS and experimental results for the testing dataset. The performance evaluation demonstrates that the ANFIS model with five inputs (Root Mean Square Error (RMSE) of 0.014) is more accurate than the ANFIS model with one input (RMSE = 0.088). The ANFIS model results are also compared with the results obtained from previous regression and soft computing studies.


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    Title :

    Improved side weir discharge coefficient modeling by adaptive neuro-fuzzy methodology



    Published in:

    Publication date :

    2016-03-04


    Size :

    7 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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