4.4 Article

Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification

期刊

STRUCTURAL ENGINEERING AND MECHANICS
卷 45, 期 6, 页码 779-802

出版社

TECHNO-PRESS
DOI: 10.12989/sem.2013.45.6.779

关键词

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

资金

  1. University of Malaya [PV043/2011B]

向作者/读者索取更多资源

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.

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