期刊文献+

基于CBR和RST的智能冲模CAD系统研究

Research on intelligent die CAD system based on Case-Based Reasoning and Rough Set Theory
下载PDF
导出
摘要 冲模设计是一个复杂的过程,严重依赖于设计者的经验,如何提高冲模设计智能化程度一直是冲模CAD领域的研究重点。本文在分析冲模的实际没计过程和智能CAD系统基础上,建立了一个基于IDEF0的冲模CAD系统功能模型,设计实现了一个基于实例推理和粗糙集理论的智能冲模CAD原型系统,并对智能冲模CAD中实例表达、实例检索、实例评价与修改等关键技术进行了研究。使用该系统能提高设计质量和效率,缩短开发周期,降低冲模生产成本。 Die design is a complex processing, and it seriously depends on the experience of the designer. How to improve the extent of the Die design intelligence which is always the keystone to research in the field of the Die CAD. In the foundation of the analysis to the practical die design processing and the intelligent CAD system, it builds a functional model based on IDEF0's Die CAD system. This paper designs and realizes a intelligentized Die CAD system based on CBR and RST. It should improve the design quality and efficiency, shorten the period of development and reduce the cost of Die using the intelligent Die CAD system.
作者 邓武
出处 《制造业自动化》 北大核心 2007年第4期44-47,78,共5页 Manufacturing Automation
基金 大连市科学基金 大连交通大学青年科技基金
关键词 智能冲模CAD 系统设计 实例推理 粗糙集 intelligent Die CAD system design Case-Based Reasoning Rough Set
  • 相关文献

参考文献4

二级参考文献22

  • 1张文修 等.Rough集理论与方法[M].北京:科学出版社,2001..
  • 2Nakasuka S,Koiskit.Automated Extraction of Attribute Hierarchies for an Improved Decision Tree Classifier.Engineering Application of Artificial Intelligence, 1995,8(4): 391-399.
  • 3Cios K J,Liu N.A Machine Learning Method for Generation of a Ncural Network Architectures:A Continuous ID3 AIgorithm.lEEE Trans. on Neural Network, 1992,(2):280-291.
  • 4Quinlan J R,lnduction of Decision Trees, Machine Lcaming, 1986, 1(1):81-106.
  • 5Hong J R.AEI:An Extension Approximate Method for Gencral Covering Problem.International Journal of Computer and Information Science, 1985,14(6):421-437.
  • 6Quinlan J R.Simplilying Decision Trees [J].Man-machine Studies.1987,27:221-234.
  • 7Pawlak Z.Rough sets[J].International Journal of Computer and Information Science,1982,11(5):341-356.
  • 8Pawlak Z.A rough set view on Bayes' theorem[J].International Journal of Intelligent Systems,2003,18(5):487-498.
  • 9Tay F,et al.Fault diagnosis based on rough set theory[J].Engineering Applications of Artificial Intelligence,2003,16(1):39-43.
  • 10Zhang T F.Dynamic system modeling based on rough sets and RBF neural networks[A].Proc of the 5th World Congress on Intelligent Control and Automation[C].Hangzhou,2004.185-189.

共引文献60

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部