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

Hossein Basser, Hojat Karami, Shahaboddin Shamshirband, Shatirah Akib, Mohsen Amirmojahedi, Rodina Ahmad, Afshin Jahangirzadeh, Hossein Javidnia

Research output: Contribution to journalArticle

Abstract

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.
Original languageEnglish
Pages (from-to)-
JournalApplied Soft Computing
DOIs
Publication statusPublished - 16 Feb 2015

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    Basser, H., Karami, H., Shamshirband, S., Akib, S., Amirmojahedi, M., Ahmad, R., Jahangirzadeh, A., & Javidnia, H. (2015). Hybrid ANFIS–PSO approach for predicting optimum parameters of a protective spur dike. Applied Soft Computing, -. https://doi.org/10.1016/j.asoc.2015.02.011