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Computers and Concrete Volume 15, Number 1, January 2015 , pages 055-71 DOI: https://doi.org/10.12989/cac.2015.15.1.055 |
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Data-driven SIRMs-connected FIS for prediction of external tendon stress |
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See Hung Lau, Chee Khoon Ng and Kai Meng Tay
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| Abstract | ||
| This paper presents a novel harmony search (HS)-based data-driven single input rule modules (SIRMs)-connected fuzzy inference system (FIS) for the prediction of stress in externally prestressed tendon. The proposed method attempts to extract causal relationship of a system from an input-output pairs of data even without knowing the complete physical knowledge of the system. The monotonicity property is then exploited as an additional qualitative information to obtain a meaningful SIRMs-connected FIS model. This method is then validated using results from test data of the literature. Several parameters, such as initial tendon depth to beam ratio; deviators spacing to the initial tendon depth ratio; and distance of a concentrated load from the nearest support to the effective beam span are considered. A computer simulation for estimating the stress increase in externally prestressed tendon, is then reported. The contributions of this paper is two folds; (i) it contributes towards a new monotonicity-preserving data-driven FIS model in fuzzy modeling and (ii) it provides a novel solution for estimating the even without a complete physical knowledge of unbonded tendons. | ||
| Key Words | ||
| bond reduction coefficient; externally prestressed tendon stress; harmony search; monotonicity index; single input rule modules (SIRMs)-connected fuzzy inference system (FIS) | ||
| Address | ||
| See Hung Lau and Chee Khoon Ng: Department of Civil Engineering, Faculty of Engineering, Universiti Malaysia Sarawak, 94300 Kota, Samarahan, Sarawak, Malaysia Kai Meng Tay: Department of Electronic Engineering, Faculty of Engineering, Universiti Malaysia Sarawak, 94300 Kota, Samarahan, Sarawak, Malaysia | ||