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Natural Hazards

, Volume 73, Issue 3, pp 1393–1404 | Cite as

Adaptive neuro-fuzzy selection of the optimal parameters of protective spur dike

  • Hossein Basser
  • Shahaboddin Shamshirband
  • Hojat Karami
  • Dalibor Petković
  • Shatirah Akib
  • Afshin Jahangirzadeh
Original Paper

Abstract

This study proposes a new approach for determining optimum dimensions of protective spur dike to mitigate scour amount around existing spur dikes. The main objective of this article was to predict the most optimum values of the protective spur dikes to reach the best performance. To predict the protective spur dike parameters for scour controlling around spur dikes, this paper constructed a process which selects the optimal protective spur dike parameters in regard to actual length of the protective spur dike, actual length of the main spur dikes, distance between the protective spur dike and the first spur dike, angle between protective spur dike and flow direction, flow intensity and median size of bed sediments with adaptive neuro-fuzzy (ANFIS) method. To build a protective spur dike with the best features, it is desirable to select and analyze factors that are truly relevant or the most influential to the spur dike. This procedure is typically called variable selection, and it corresponds to finding a subset of the full set of recorded variables that exhibits good predictive abilities. In this study, architecture for modeling complex systems in function approximation and regression was used, based on using ANFIS. Variable searching using the ANFIS network was performed to determine how the five factors affect the protective spur dike. Experimental model of the protective spur dike was used to generate training and checking data for the ANFIS network.

Keywords

Scour Protective spur dike Variable selection Neuro-fuzzy ANFIS 

Notes

Acknowledgments

Authors would like to acknowledge the Bright Sparks Program at University of Malaya. Also, the financial support by the high impact research grants of the University of Malaya (UM.C/625/1/HIR/116, account number: J-16002-00-7383000-000000) and (UM.C/625/1/HIR/61, account number: H-16001-00-D000061) is gratefully acknowledged. Authors also want to thank the partial support of Amirkabir University of Technology for the experimental facilities.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Hossein Basser
    • 1
  • Shahaboddin Shamshirband
    • 2
  • Hojat Karami
    • 3
  • Dalibor Petković
    • 4
  • Shatirah Akib
    • 1
  • Afshin Jahangirzadeh
    • 1
  1. 1.Department of Civil EngineeringUniversity of MalayaKuala LumpurMalaysia
  2. 2.Department of Computer System and Technology, Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala LumpurMalaysia
  3. 3.Department of Civil EngineeringSemnan UniversitySemnanIran
  4. 4.Department for Mechatronics and Control, Faculty of Mechanical EngineeringUniversity of NišNisSerbia

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