Hybrid ANFIS-PSO approach for predicting optimum parameters of a protective spur dike

被引:61
作者
Basser, Hossein [1 ]
Karami, Hojat [2 ]
Shamshirband, Shahaboddin [3 ]
Akib, Shatirah [1 ]
Amirmojahedi, Mohsen [1 ]
Ahmad, Rodina [4 ]
Jahangirzadeh, Afshin [1 ]
Javidnia, Hossein [5 ]
机构
[1] Univ Malaya, Dept Civil Engn, Kuala Lumpur 50603, Malaysia
[2] Semnan Univ, Dept Civil Engn, Semnan, Iran
[3] Univ Malaya, Fac Comp Sci & Informat Technol, Dept Comp Syst & Informat Technol, Kuala Lumpur 50603, Malaysia
[4] Univ Malaya, Fac Comp Sci & Informat Technol, Dept Software Engn, Kuala Lumpur 50603, Malaysia
[5] NUI, Dept Engn & Informat, Elect & Elect Engn, Galway, Ireland
关键词
Scour; Swarm optimization; Prediction; Neuro-fuzzy; PARTICLE SWARM OPTIMIZATION; SCOUR DEPTH; NEURAL-NETWORK; FAILURE;
D O I
10.1016/j.asoc.2015.02.011
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this study a new approach was proposed to determine optimum parameters of a protective spur dike to mitigate scouring depth amount around existing main spur dikes. The studied parameters were angle of the protective spur dike relative to the flume wall, its length, and its distance from the main spur dikes, flow intensity, and the diameters of the sediment particles that were explored to find the optimum amounts. In prediction phase, a novel hybrid approach was developed, combining adaptive-network-based fuzzy inference system and particle swarm optimization (ANFIS-PSO) to predict protective spur dike's parameters in order to control scouring around a series of spur dikes. The results indicated that the accuracy of the proposed method is increased significantly compared to other approaches. In addition, the effectiveness of the developed method was confirmed using the available data. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:642 / 649
页数:8
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