Techno Press
Techno Press

Steel and Composite Structures   Volume 9, Number 5, October 2009, pages 445-455
DOI: http://dx.doi.org/10.12989/scs.2009.9.5.445
 
Iterative neural network strategy for static model identification of an FRP deck
Dookie Kim, Dong Hyawn Kim, Jintao Cui, Hyeong Yeol Seo and Young Ho Lee

 
Abstract     [Full Text]
    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
 

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