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

被引：0
作者：
Shahaboddin Shamshirband
Hossein Bonakdari
Amir Hossein Zaji
Dalibor Petkovic
Shervin Motamedi
机构：
[1] University of Malaya,Dept. of Computer System, Faculty of Computer Science and Information Technology
[2] Razi University,Dept. of Civil Engineering
[3] University of Nis,Faculty of Mechanical Engineering, Dept. of Mechatronics and Control
[4] University of Malaya,Institute of Ocean and Earth Sciences
来源：
KSCE Journal of Civil Engineering | 2016年 / 20卷
关键词：
ANFIS; soft computing; discharge coefficient; triangular side weir; modeling; input combination;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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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页码：2999 / 3005
页数：6
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