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Steel and Composite Structures Volume 9, Number 5, October 2009 , pages 445-455 DOI: https://doi.org/10.12989/scs.2009.9.5.445 |
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Iterative neural network strategy for static model identification of an FRP deck |
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Dookie Kim, Dong Hyawn Kim, Jintao Cui, Hyeong Yeol Seo and Young Ho Lee
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Abstract | ||
This study proposes a system identification technique for a fiber-reinforced polymer deck with neural networks. Neural networks are trained for system identification and the identified structure gives training data in return. This process is repeated until the identified parameters converge. Hence, the proposed algorithm is called an iterative neural network scheme. The proposed algorithm also relies on recent developments in the experimental design of the response surface method. The proposed strategy is verified with known systems and applied to a fiber-reinforced polymer bridge deck with experimental data. | ||
Key Words | ||
fiber-reinforced polymer (FRP); system identification; neural network (NN); response surface method (RSM); iteration. | ||
Address | ||
Dookie Kim; Department of Civil and Environmental Engineering, Kunsan National University, Kunsan, Jeonbuk, Korea Dong Hyawn Kim; 2Department of Coastal Construction Engineering, Kunsan National University, Kunsan, Jeonbuk, Korea Jintao Cui; Department of Civil and Environmental Engineering, Kunsan National University, Kunsan, Jeonbuk, Korea Hyeong Yeol Seo; Department of Civil and Environmental Engineering, Kunsan National University, Kunsan, Jeonbuk, Korea Young Ho Lee; Structure Research Department, Korea Institute of Construction Technology, Goyang, Gyeonggi, Korea | ||