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    Title: Optimal Design of Plane Frame Structures Using Artificial Neural Networks and Ratio Variables
    Authors: Kao, Chin-Sheng;Yeh, I-Cheng
    Keywords: artificial neural networks;optimization;plane frame;ratio variable
    Date: 2014-11-01
    Issue Date: 2016-01-06 11:06:16 (UTC+8)
    Abstract: There have been many packages that can be employed to analyze plane frames. However, because most structural analysis packages suffer from closeness of system, itis very difficult to integrate it with an optimization package. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrate Design, Analysis, Modeling, Definition, and Optimization phases into an integrative environment. The DAMDO methodology employs neural networks to integrate structural analysis package and optimization package so as not to need directly to integrate these two packages. The key problem of the DAMDO approach is how to generate a set of reasonable random designsin the first phase. According to the characteristics of optimized plane frames, we proposed the ratio variable approach to generate them. The empirical results show that the ratio variable approach can greatly improve the accuracy of the neural networks, and the plane frame optimization problems can be solved by the DAMDO methodology.
    Relation: Structural Engineering and Mechanics 52(4), pp.739-753
    DOI: 10.12989/sem.2014.52.4.739
    Appears in Collections:[土木工程學系暨研究所] 期刊論文

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