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Structural Engineering and Mechanics
  Volume 45, Number 6, March25 2013, pages 779-802
DOI: http://dx.doi.org/10.12989/sem.2013.45.6.779
 


Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification
S.J.S. Hakim and H. Abdul Razak

 
Abstract
    In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANNs) techniques are developed and applied to identify damage in a model steel girder bridge using dynamic parameters. The required data in the form of natural frequencies are obtained from experimental modal analysis. A comparative study is made using the ANNs and ANFIS techniques and results showed that both ANFIS and ANN present good predictions. However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. This paper also highlights the concept of ANNs and ANFIS followed by the detail presentation of the experimental modal analysis for natural frequencies extraction.
 
Key Words
    adaptive neuro fuzzy interface system (ANFIS); artificial neural networks (ANNs); backpropagation (BP); damage identification; experimental modal analysis
 
Address
S.J.S. Hakim and H. Abdul Razak: StrucHMRS Group, Department of Civil Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
 

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