Hakim, S.J.S. and Abdul Razak, H. (2013) Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification. Structural Engineering and Mechanics, 45 (6). pp. 779-802. ISSN 1225-4568,
Full text not available from this repository.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.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Additional Information: | 230IF Times Cited:1 Cited References Count:53 |
| Uncontrolled Keywords: | adaptive neuro fuzzy interface system (anfis), artificial neural networks (anns), backpropagation (bp), damage identification, experimental modal analysis, rotating machinery, fault-diagnosis, prediction, beams, strength, logic |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Faculty of Engineering |
| Depositing User: | Mr Jenal S |
| Date Deposited: | 24 Jan 2014 14:53 |
| Last Modified: | 29 Oct 2014 06:44 |
| URI: | http://eprints.um.edu.my/id/eprint/9054 |
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