Mechanical Product Green Design Knowledge Update Based on Rough Set

被引:2
|
作者
Zhang L. [1 ]
Zheng C. [1 ]
Zhong Y. [1 ]
Qin X. [1 ]
机构
[1] School of Mechanical Engineering, Hefei University of Technology, Hefei
关键词
Decision rule; Green design; Knowledge update; Ontology; Rough set;
D O I
10.3969/j.issn.1004-132X.2019.05.013
中图分类号
学科分类号
摘要
In order to meet the green demands of modern product design, it is particularly important to update the knowledges of mechanical product green design in time. Based on ontology, the green design knowledges of mechanical products were expressed and the decision tables of green design knowledges of mechanical products were built through rough sets. The rules of green product design knowledges were extracted and the rule set of green design knowledges of mechanical products was established. Combined with the knowledge needs of designers, the knowledge update in the mechanical product green design processes was realized through the matching of green design knowledge rules. Finally, the proposed methodology was successfully applied to the piston green design knowledge processes update. © 2019, China Mechanical Engineering Magazine Office. All right reserved.
引用
收藏
页码:595 / 602
页数:7
相关论文
共 11 条
  • [1] Wang Y., Yu S., Xu T., A User Requirement Driven Framework for Collaborative Design Knowledge Management, Advanced Engineering Informatics, 33, pp. 16-28, (2017)
  • [2] Hatzilygeroudis I., Prentzas J., Using a Hybrid Rule-based Approach in Developing an Intelligent Tutoring System with Knowledge Acquisition and Update Capabilities, Expert Systems with Applications, 26, 4, pp. 477-492, (2004)
  • [3] Xu J., Qiu L.M., Zhang S.Y., Progressive Product Configuration Design Technology Based on Knowledge Feedback, Computer Integrated Manufacturing Systems, 17, 6, pp. 1135-1143, (2011)
  • [4] Chen J., Yang H., Dong M., Et al., Update of Design Knowledge Based on Similarity Matching of Ontology Semantic Blocks, Journal of Mechanical Engineering, 50, 7, pp. 161-167, (2014)
  • [5] Pawlak Z., Rough Sets: Theoretical Aspects of Reasoning about Data, (1992)
  • [6] Li J.H., Mei C.L., Lyu Y.J., A Heuristic Knowledge-reduction Method for Decision Formal Contexts, Computers & Mathematics with Applications, 61, 4, pp. 1096-1106, (2011)
  • [7] Li Z., Suitability of Fuzzy Reasoning Methods, Fuzzy Sets & Systems, 108, 3, pp. 299-311, (1999)
  • [8] Shi B., Li G., Wu W., Et al., Attribute Reduction Method Based on Enhanced Positive Domain, Application Research of Computers, 34, 1, pp. 107-109, (2017)
  • [9] Dai J., Pan Y., A Decision Rules Acquisition Algorithm Based on Classification Consistency, Control and Decision, 19, 10, pp. 1086-1090, (2004)
  • [10] Lu X., Gao P., Zhou Q., Research on Rule Mining Algorithm Based on Coherence of Rough Sets Classification-The Risk of Knowledge Transfer in IT Outsourcing, Computer Engineering and Applications, 49, 6, pp. 217-220, (2013)