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JACIII Vol.20 No.2 pp. 355-377
doi: 10.20965/jaciii.2016.p0355
(2016)

Paper:

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Multi-Level Control of Fuzzy-Constraint Propagation via Evaluations with Linguistic Truth Values in Generalized-Mean-Based Inference

Kiyohiko Uehara* and Kaoru Hirota**

*Ibaraki University
Hitachi 316-8511, Japan

**Beijing Institute of Technology
Beijing 100081, China

Received:
November 30, 2015
Accepted:
January 21, 2016
Online released:
March 18, 2016
Published:
March 20, 2016
Creative Commons License
Keywords:
fuzzy inference, compositional rule of inference, implication, convex fuzzy set, α-cut
Abstract
A method is proposed for fuzzy inference which can propagate convex fuzzy-constraints from given facts to consequences in various forms by applying a number of fuzzy rules, particularly when asymmetric fuzzy sets are used for given facts and/or fuzzy rules. The conventionalmethod, α-GEMS (α-level-set and generalized-mean-based inference in synergy with composition), cannot be performed with asymmetric fuzzy sets; it can be conducted only with symmetric fuzzy sets. In order to cope with asymmetric fuzzy sets as well as symmetric ones, a control scheme is proposed for the fuzzy-constraint propagation, which is α-cut based and can be performed independently at each level of α. It suppresses an excessive specificity decrease in consequences, particularly stemming from the asymmetricity. Thereby, the fuzzy constraints of given facts are reflected to those of consequences, to a feasible extent. The theoretical aspects of the control scheme are also presented, wherein the specificity of the support sets of consequences is evaluated via linguistic truth values (LTVs). The proposed method is named α-GEMST (α-level-set and generalized-meanbased inference in synergy with composition via LTV control) in order to differentiate it from α-GEMS. Simulation results show that α-GEMST can be properly performed, particularly with asymmetric fuzzy sets. α-GEMST is expected to be applied to the modeling of given systems with various fuzzy input-output relations.
Cite this article as:
K. Uehara and K. Hirota, “Multi-Level Control of Fuzzy-Constraint Propagation via Evaluations with Linguistic Truth Values in Generalized-Mean-Based Inference,” J. Adv. Comput. Intell. Intell. Inform., Vol.20 No.2, pp. 355-377, 2016.
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