[KSCI] Korea Science Citation Index Service

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

Hakim, S.J.S. (StrucHMRS Group, Department of Civil Engineering, University of Malaya)
Razak, H. Abdul (StrucHMRS Group, Department of Civil Engineering, University of Malaya)

Publication Information

Structural Engineering and Mechanics / v.45, no.6, 2013 , pp. 779-802 More about this Journal

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.

Keywords

adaptive neuro fuzzy interface system (ANFIS); artificial neural networks (ANNs); backpropagation (BP); damage identification; experimental modal analysis;

Citations & Related Records

Times Cited By KSCI : 4 (Citation Analysis)

Reference
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1	Identification of a suitable ANN architecture in predicting strain in tie section of concrete deep beams / [Mohammadhassani, Mohammad;Nezamabadi-pour, Hossein;Suhatril, Meldi;Shariati, Mahdi;] / Structural Engineering and Mechanics
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