한국전산구조공학회:학술대회논문집 (Proceedings of the Computational Structural Engineering Institute Conference)
- 한국전산구조공학회 1999년도 가을 학술발표회 논문집
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- Pages.387-394
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- 1999
인공신경망을 이용한 이력모델에 관한 연구
A Study on the Hysteretic Model using Artificial Neural Network
초록
Artificial Neural Network (ANN) is a computational model inspired by the structure and operations of the brain. It is massively parallel system consisting of a large number of highly interconnected and simple processing units. The purpose of this paper is to verify the applicability of ANN to predict experimental results through the use of measured experimental data. Although there have been accumulated data based on hysteretic characteristics of structural element with cyclic loading tests, it is difficult to directly apply them for the analysis of elastic and plastic response. Thus, simple models with mathematical formula such as Bi-Linear Model, Ramberg-Osgood Model, Degrading Tri Model, Takeda Model, Slip type Model, and etc, have been used. To verify the practicality and capability of this study, ANN is adapted to several models with mathematical formula using numerical data To show the efficiency of ANN in nonlinear analysis, it is important to determine the adequate input and output variables of hysteretic models and to minimize an error in ANN process. The application example is Beam-Column joint test using the ANN in modeling of the linear and nonlinear hysteretic behavior of structure.
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