Paper Info
Title
An Interval Approach To Fuzzistics For Interval Type-2 Fuzzy Sets
Abstract
In this paper, a new and simple approach, called Interval Approach, to type-2 fuzzistics is presented, one that captures the strong points of both the person-MF and interval end-points approaches. It uses interval end-point data that are collected from a group of subjects, assumes a probability distribution for each person's data and maps the mean and standard deviation of that distribution into the parameters of an iteratively specified type-1 person MF. These type-1 person MFs are then aggregated using the union leading to the FOU for a word. Experiments show that this approach is easy to implement and the derived interval type-2 word models match our intuitions, i.e., the FOUs of the small-sounding words are located to the left, the FOUs of the medium-sounding words are located in the middle, and the FOUs of the large-sounding words are located to the right.
Year
DOI
Venue
2007
10.1109/FUZZY.2007.4295508
2007 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-4
Keywords
Field
DocType
engines,fuzzy sets,natural languages,signal processing,probability distribution,image processing,uncertainty,fuzzy set theory,statistical distributions,computer architecture,standard deviation,decoding
Signal processing,Intuition,Image processing,Fuzzy set,Probability distribution,Natural language,Artificial intelligence,Decoding methods,Standard deviation,Machine learning,Mathematics
Conference
ISSN
Citations 
PageRank 
1098-7584
26
1.28
References 
Authors
11
2
Name
Order
Citations
PageRank
Feilong Liu142915.52
Mendel, J.M.2109261042.42