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논문 기본 정보

자료유형
학술저널
저자정보
Kangkang Yang (Wuhan University) Shijing Wu (Wuhan University) Wenqiang Zhao (Wuhan University) Lu Zhou (Wuhan University)
저널정보
Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.9 No.2
발행연도
2015.6
수록면
98 - 107 (10page)

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초록· 키워드

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Hierarchical constraints and constraint satisfaction were analyzed in order to solve the problem of conflict detection in collaborative design. The constraints were divided into two sets: one set consisted of known constraints and the other of unknown constraints. The constraints of the two sets were detected with corresponding methods. The set of the known constraints was detected using an interval propagation algorithm, a back propagation (BP) neural network was proposed to detect the set with the unknown constraints. An immune algorithm (IA) was utilized to optimize the weights and the thresholds of the BP neural network, and the steps were designed for the optimization process. The results of the simulation indicated that the BP neural network that was optimized by IA has a better performance in terms of convergent speed and global searching ability than a genetic algorithm. The constraints were described using the eXtensible Markup Language (XML) for computers to be able to automatically recognize and establish the constraint network. The implementation of the conflict detection system was designed based on constraint satisfaction. A wind planetary gear train is taken as an example of collaborative design with a conflict detection system.

목차

Abstract
Ⅰ. INTRODUCTION
Ⅱ. CONSTRAINT ANALYSIS OF COLLABORATIVE DESIGN
Ⅲ. DESIGN OF THE CONFLICT DETECTION MODEL
Ⅳ. DESIGN AND IMPLEMENTATION OF CONFLICT DETECTION SYSTEM
Ⅴ. CONCLUSION
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UCI(KEPA) : I410-ECN-0101-2016-569-001673835