Title :
Using artificial neural networks to develop a mechanism for functional feature-based reference design retrieval
Author :
Chen, Y.J. ; Chen, Y.M. ; Wang, C.B. ; Chen, T.
Author_Institution :
Inst. of Manuf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
This study uses the adaptive resonance theory (ART) neural network to realize a mechanism for functional feature-based reference design retrieval to provide engineering designers with easy access to relevant design and related knowledge. The retrieval process includes the steps of functional feature-based query, case searching, and case ranking. The technology involves a binary code-based representation for functional features, ART neural network for functional feature-based case clustering, functional feature-based case similarity ranking, and a case-based representation for designed entities.
Keywords :
ART neural nets; binary codes; design engineering; information retrieval; knowledge engineering; knowledge management; statistical analysis; ART; adaptive resonance theory; artificial neural networks; binary code-based representation; case clustering; case ranking; case searching; case similarity ranking; case-based representation; engineering designers; functional feature-based reference design retrieval; knowledge management; knowledge retrieval; Artificial neural networks; Design engineering; Design methodology; Information retrieval; Knowledge engineering; Knowledge management; Manufacturing; Neural networks; Product design; Subspace constraints;
Conference_Titel :
Engineering Management Conference, 2004. Proceedings. 2004 IEEE International
Print_ISBN :
0-7803-8519-5
DOI :
10.1109/IEMC.2004.1407497