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Kazuhisa Niwa, Ichizou Mikami

Prediction of ultimate strength of steel orthogonally stiffened plates subjected to compression using neural network system -

Abstract: A neural network system has been developed for predicting ultimate strength of orthogonally stiffened plates subjected to uniaxial compression. The system learned many experimental results with respect to load carrying capacity of steel stiffened plates, which were collected by the authors throughout the world. The system can accurately infer ultimate strength for all the learning cases. The system will be able to simulate experiments for the various cases.

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Series: ecce:1997 (browse)
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Shigenori Tanaka, Ichizou Mikami

A kbes combining cbr and rbr to select repalr and retftoflt methods for fatigue damage on steel bridges

Abstract: We have studied the knowledgebased expert system (KBES) to select repairing and retrofitting methods for fatigue damage of steel bridges. The case-based reasoning (CBR) system can solve the problem of howledge acquisition and perform efficient inference based on similar cases, w h e m the rulebased reasoning (RBR) system has the difficulty in acquiring knowledge bases. In the present paper, we constructed a KBES, in whicb CBR and RBR were combined, to select repairing and retrofitting methods for steel bridges‘ fatigue damage. The inference results obtained from this system are discussed to prove its usefulness, and subjects for the future are identified.

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