Information Sciences: an International Journal
Information Sciences: an International Journal
Fuzzy subsethood for fuzzy sets of type-2 and generalized type-n
IEEE Transactions on Fuzzy Systems
Historical reflections and new positions on perceptual computing
Fuzzy Optimization and Decision Making
Similarity-based perceptual reasoning for perceptual computing
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Perceptual reasoning for perceptual computing: a similarity-based approach
IEEE Transactions on Fuzzy Systems
Obtaining an FOU for a word from a single subject by an individual interval approach
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Uncertainty measures for general type-2 fuzzy sets
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Computing with words for hierarchical decision making applied to evaluating a weapon system
IEEE Transactions on Fuzzy Systems - Special section on computing with words
IEEE Transactions on Fuzzy Systems - Special section on computing with words
New linguistic hedges in construction of interval type-2 FLS
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Uncertainty measures for general Type-2 fuzzy sets
Information Sciences: an International Journal
Conceptual design evaluation using interval type-2 fuzzy information axiom
Computers in Industry
Expert Systems with Applications: An International Journal
Fuzzy rule interpolation based on the ratio of fuzziness of interval type-2 fuzzy sets
Expert Systems with Applications: An International Journal
How to handle uncertainties in AHP: The Cloud Delphi hierarchical analysis
Information Sciences: an International Journal
Median interval approach to model words with interval type-2 fuzzy sets
International Journal of Advanced Intelligence Paradigms
Novel Weighted Averages versus Normalized Sums in Computing with Words
Information Sciences: an International Journal
A reconstruction decoder for computing with words
Information Sciences: an International Journal
Fixed charge transportation problem with type-2 fuzzy variables
Information Sciences: an International Journal
Uncertainty degree and modeling of interval type-2 fuzzy sets: Definition, method and application
Computers & Mathematics with Applications
Interval type-2 fuzzy logic for encoding clinical practice guidelines
Knowledge-Based Systems
Hi-index | 0.00 |
This paper presents a very practical type-2-fuzzistics methodology for obtaining interval type-2 fuzzy set (IT2 FS) models for words, one that is called an interval approach (IA). The basic idea of the IA is to collect interval endpoint data for a word from a group of subjects, map each subject's data interval into a prespecified type-1 (T1) person membership function, interpret the latter as an embedded T1 FS of an IT2 FS, and obtain a mathematical model for the footprint of uncertainty (FOU) for the word from these T1 FSs. The IA consists of two parts: the data part and the FS part. In the data part, the interval endpoint data are preprocessed, after which data statistics are computed for the surviving data intervals. In the FS part, the data are used to decide whether the word should be modeled as an interior, left-shoulder, or right-shoulder FOU. Then, the parameters of the respective embedded T1 MFs are determined using the data statistics and uncertainty measures for the T1 FS models. The derived T1 MFs are aggregated using union leading to an FOU for a word, and finally, a mathematical model is obtained for the FOU. In order that all researchers can either duplicate our results or use them in their research, the raw data used for our codebook examples, as well as a MATLAB M-file for the IA, have been put on the Internet at: http://sipi.usc.edu/ ~ mendel.