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- Title
Soft computing methodologies for estimation of bridge girder forces with perforations under tsunami wave loading.
- Authors
Akib, Shatirah; Rahman, Sadia; Shamshirband, Shahaboddin; Petković, Dalibor
- Abstract
Tsunamis pose a great threat to coastal infrastructures. Bridges without adequate provisions for earthquake and tsunami loading generally are vulnerable when a tsunami occurs. During the last two disastrous tsunami events (i.e., the tsunami in the Indian Ocean and the tsunami that struck Japan), many bridges were damaged by the waves created by the tsunamis. In this paper, in order to address this crucial problem, we used soft computing techniques to design and develop a process that simulates the effects of perforations in the girders of bridges on reducing the forces applied on the bridge when a tsunami occurs. Soft computing methods have very good learning and prediction capabilities, which make it an effective tool for dealing with the uncertainties encountered when waves are generated by a tsunami. Laboratory experiments were conducted to acquire a better understanding of the effects of the factors involved and to check the data required for the soft computing methods. In order to predict the effects of perforations in the girder of a bridge on force reduction, novel intelligent soft computing schemes, support vector regression (SVR), and adaptive neuro-fuzzy inference system (ANFIS) were investigated. In this study, the polynomial, linear, and radial basis function were used as the kernel function of the SVR to estimate the effects of perforations in a girder of a bridge. The performances of the proposed estimators were confirmed by simulation results. The SVR results were compared with the ANFIS results, and we observed that an improvement in predictive accuracy and the ability to generalize were achieved by the ANFIS approach.
- Subjects
INDIAN Ocean; BRIDGE design &; construction; TSUNAMIS; NATURAL disasters; COASTAL engineering
- Publication
Bulletin of Earthquake Engineering, 2015, Vol 13, Issue 3, p935
- ISSN
1570-761X
- Publication type
Article
- DOI
10.1007/s10518-014-9656-3