International Journal of Computational Intelligence Systems

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Volume 9, Issue Supplement 1, April 2016, Pages 35 - 42

From Fuzzy Models to Granular Fuzzy Models

Authors
Witold Pedrycz[email protected]
Department of Electrical & Computer Engineering, University of Alberta, Edmonton T6R 2V4 AB Canada, Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia and Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland
Received 28 November 2015, Accepted 8 March 2016, Available Online 1 April 2016.
DOI
10.1080/18756891.2016.1180818How to use a DOI?
Keywords
fuzzy models; Granular Computing; information granules of higher type; granular spaces
Abstract

In this study, we offer a general view at the area of fuzzy modeling and elaborate on a new direction of system modeling by introducing a concept of granular models. Those models constitute a generalization of existing fuzzy models and, in contrast to existing models, generate results in the form of information granules (such as intervals, fuzzy sets, rough sets and others). We present a rationale and some key motivating arguments behind the emergence of granular models and discuss their underlying design process. Central to the development of granular models are granular spaces, namely a granular space of parameters of the models and a granular input space. The development of the granular model is completed through an optimal allocation of information granularity, which optimizes criteria of coverage and specificity of granular information. The emergence of granular models of type-2 and type-n, in general, is discussed along with an elaboration on their formation. It is shown that achieving a sound coverage-specificity tradeoff (compromise) is of essential relevance in the realization of the granular models.

Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
9 - Supplement 1
Pages
35 - 42
Publication Date
2016/04/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2016.1180818How to use a DOI?
Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Witold Pedrycz
PY  - 2016
DA  - 2016/04/01
TI  - From Fuzzy Models to Granular Fuzzy Models
JO  - International Journal of Computational Intelligence Systems
SP  - 35
EP  - 42
VL  - 9
IS  - Supplement 1
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2016.1180818
DO  - 10.1080/18756891.2016.1180818
ID  - Pedrycz2016
ER  -