Application of the ANFIS model in deflection prediction of concrete deep beam
Article
Article Title | Application of the ANFIS model in deflection prediction of concrete deep beam |
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ERA Journal ID | 3821 |
Article Category | Article |
Authors | Mohammadhassani, Mohammad, Nezamabadi-Pour, Hossein, Jumaat, Mohd Zamin, Jameel, Mohammed, Hakim, S. J. S. and Zargar, Majid |
Journal Title | Structural Engineering and Mechanics |
Journal Citation | 45 (3), pp. 323-336 |
Number of Pages | 14 |
Year | 2013 |
Place of Publication | Korea |
ISSN | 1225-4568 |
1598-6217 | |
Digital Object Identifier (DOI) | https://doi.org/10.12989/sem.2013.45.3.323 |
Web Address (URL) | http://www.koreascience.or.kr/article/JAKO201315541091396.page |
Abstract | With the ongoing development in the computer science areas of artificial intelligence and computational intelligence, researchers are able to apply them successfully in the construction industry. Given the complexities indeep beam behaviour and the difficulties in accurate evaluation of its deflection, the current study has employed the Adaptive Network-based Fuzzy Inference System (ANFIS) as one of the modelling tools to predict deflection for high strength self compacting concrete (HSSCC) deep beams. In this study, about 3668measured data on eight HSSCC deep beams are considered. Effective input data and the corresponding deflection as output data were recorded at all loading stages up to failure load for all tested deep beams. The results of ANFIS modelling and the classical linear regression were compared and concluded that the ANFIS results are highly accurate, precise and satisfactory. |
Keywords | ANFIS; Deep beams; Deflection; Fuzzy inference system; Linear regression |
Public Notes | There are no files associated with this item. |
Byline Affiliations | University of Malaya, Malaysia |
Shahid Bahonar University of Kerman, Iran | |
Library Services |
https://research.usq.edu.au/item/w752q/application-of-the-anfis-model-in-deflection-prediction-of-concrete-deep-beam
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