DocumentCode
1642040
Title
Rule approximation in metric spaces
Author
Kovács, L.
Author_Institution
Dept. of Inf. Technol., Univ. of Miskolc, Miskolc, Hungary
fYear
2010
Firstpage
49
Lastpage
52
Abstract
The classical fuzzy rule interpolators work in Euclidean spaces where the new fuzzy value can be generated from the training values. The paper investigates the case when the fuzzy values are defined over the general metric spaces. In this case a classification process is used to approximate the requested value. The paper introduces a base method for this classification process.
Keywords
fuzzy reasoning; fuzzy set theory; interpolation; pattern classification; Euclidean spaces; classification process; fuzzy rule interpolators; fuzzy value; metric spaces; rule approximation; Bismuth; Extraterrestrial measurements; Fuzzy sets; Informatics; Information technology; Interpolation; Machine intelligence; Shape; Space technology; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Applied Machine Intelligence and Informatics (SAMI), 2010 IEEE 8th International Symposium on
Conference_Location
Herlany
Print_ISBN
978-1-4244-6422-7
Type
conf
DOI
10.1109/SAMI.2010.5423702
Filename
5423702
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