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Content Provider | IEEE Xplore Digital Library |
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Author | Jie Hu Jilong Yin Yinghong Peng Dayong Li |
Copyright Year | 2006 |
Description | Author affiliation: Sch. of Mech. Eng., Shanghai Jiao Tong Univ. (Jie Hu; Jilong Yin; Yinghong Peng; Dayong Li) |
Abstract | Knowledge-based engineering (KBE) and simulation analysis have been used widely in multidisciplinary concurrent and collaborative design process. However, the acquisition of knowledge keeps bottleneck yet in building knowledge base in KBE. In this paper, a framework of knowledge discovery from multidisciplinary simulation data is proposed. Correspondingly, a data mining algorithm named fuzzy-rough algorithm is developed to deal with the simulation data by combining the fuzzy set theory and rough set theory. The proposed knowledge discovery process is applied respectively to obtain some useful, implicit production rules with efficient measure. Finally, the method is demonstrated by a metal forming simulation problem. The results prove that knowledge discovery from simulation data is feasible, and the proposed method can be applied in other disciplinary simulation |
Sponsorship | IEEE Beijing Section |
Starting Page | 1 |
Ending Page | 6 |
File Size | 1074385 |
Page Count | 6 |
File Format | |
ISBN | 142440164X |
DOI | 10.1109/CSCWD.2006.253177 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2006-05-03 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Collaboration Design engineering Knowledge engineering Analytical models Process design Buildings Data mining Fuzzy set theory Set theory Production Concurrent and Collaborative Design Knowledge Discovery Multidisciplinary Simulation |
Content Type | Text |
Resource Type | Article |
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