Paper Info
Title
Aggregation Using the Fuzzy Weighted Average as Computed by the Karnik–Mendel Algorithms
Abstract
By connecting work from two different problems-the fuzzy weighted average (FWA) and the generalized centroid of an interval type-2 fuzzy set-a new alpha-cut algorithm for solving the FWA problem has been obtained, one that is monotonically and superexponentially convergent. This new algorithm uses the Karnik-Mendel (KM) algorithms to compute the FWA -cut end-points. It appears that the KM -cut algorithms approach for computing the FWA requires the fewest iterations to date, and may therefore be the fastest available FWA algorithm to date.
Year
DOI
Venue
2008
10.1109/TFUZZ.2007.896229
IEEE T. Fuzzy Systems
Keywords
Field
DocType
fuzzy weighted average,problems-the fuzzy weighted average,fastest available fwa algorithm,superexponentially convergent,algorithms approach,fewest iteration,fwa problem,new algorithm,cut end-points,mendel algorithms,fuzzy set-a new alpha-cut,generalized centroid,fuzzy sets,centroid,arithmetic,fuzzy logic,signal processing,uncertainty,fuzzy set theory,fuzzy systems,mathematical model
Fuzzy weighted average,Signal processing,Fuzzy set,Artificial intelligence,Fuzzy control system,Monotonic function,Mathematical optimization,Perceptual computing,Fuzzy logic,Algorithm,Machine learning,Centroid,Mathematics
Journal
Volume
Issue
ISSN
16
1
1063-6706
Citations 
PageRank 
References 
66
2.55
8
Authors
2
Name
Order
Citations
PageRank
Feilong Liu142915.52
Mendel, J.M.2109261042.42