DocumentCode
3263172
Title
Machine learning in engineering design-an unsupervised fuzzy neural network case-based learning model
Author
Hung, Shih-Lin ; Jan, J.C.
Author_Institution
Dept. of Civil Eng., Nat. Chiao Tung Univ., Taiwan
fYear
35765
fDate
8-10 Dec1997
Firstpage
156
Lastpage
160
Abstract
Engineering design is a creative and experience oriented process. Facing a new design case, an experienced designer will recall the similar cases in a case base which have been solved before. Then, the designer will attempt to find the solution from these similar cases in a way of adaptation or synthesis. An unsupervised fuzzy neural network (UFN) case-based learning model has been developed to perform the aforementioned design process and implemented in two steps. The UFN learning model has been applied to the domain of engineering design. The learning results show that the learning performance of the new learning model is superior to that of a supervised learning model only in complicated or discrete domains. Also, the unsupervised fuzzy neural network learning model can learn complicated design problems within a reasonable CPU time
Keywords
adaptive systems; case-based reasoning; computer aided engineering; fuzzy neural nets; intelligent design assistants; learning systems; CPU time; adaptation; case base; creative process; engineering design; experience oriented process; learning performance; machine learning; synthesis; unsupervised fuzzy neural network case-based learning model; Design engineering; Fuzzy neural networks; Intelligent networks; Knowledge engineering; Machine learning; Network synthesis; Neural networks; Process design; Structural engineering; Supervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Information Systems, 1997. IIS '97. Proceedings
Conference_Location
Grand Bahama Island
Print_ISBN
0-8186-8218-3
Type
conf
DOI
10.1109/IIS.1997.645209
Filename
645209
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