DocumentCode
3108713
Title
Efficiently comparing fuzzy graphs
Author
Berthold, Michael R. ; Huber, Klaus-Peter
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
fYear
1998
fDate
20-21 Aug 1998
Firstpage
208
Lastpage
211
Abstract
The paper investigates techniques for comparing two fuzzy graphs. Fuzzy graphs are attracting attention because they not only allow easy interpretation but in addition finding regions of interest or tolerating missing attributes can be done computationally in a very efficient manner. This is of great interest in numerous applications such as intelligent data analysis, meta-modeling and others. Two ways of comparing fuzzy graphs are presented
Keywords
fuzzy logic; graph theory; efficient fuzzy graph comparison; intelligent data analysis; meta-modeling; missing attribute tolerance; regions of interest; Computational efficiency; Computational intelligence; Computer science; Data analysis; Equations; Fuzzy systems; Input variables; Metamodeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society - NAFIPS, 1998 Conference of the North American
Conference_Location
Pensacola Beach, FL
Print_ISBN
0-7803-4453-7
Type
conf
DOI
10.1109/NAFIPS.1998.715566
Filename
715566
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