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
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;
Conference_Titel :
Fuzzy Information Processing Society - NAFIPS, 1998 Conference of the North American
Conference_Location :
Pensacola Beach, FL
Print_ISBN :
0-7803-4453-7
DOI :
10.1109/NAFIPS.1998.715566
