NDLI: Inference methods for systems with many fuzzy inputs

Content Provider	Springer Nature Link
Author	Kutsenko, D. A. Sinyuk, V. G.
Copyright Year	2015
Abstract	In fuzzy simulation, both crisp and fuzzy information can be input into simulated fuzzy systems. The known methods of fuzzy inference for fuzzy input values either have low computational efficiency or do not allow using the whole diversity of logical operations. In this paper, a new method of logical inference is described based on a fuzzy degree of truth for systems with many inputs at which fuzzy input values are received. The method is compared with the initial Zadeh method and the popular Mamdani method. The computational efficiency of the proposed method is also shown. The method is generalized to systems with a block of rules.
Starting Page	375
Ending Page	383
Page Count	9
File Format	PDF
ISSN	10642307
Journal	Journal of Computer and Systems Sciences International
Volume Number	54
Issue Number	3
e-ISSN	15556530
Language	English
Publisher	Pleiades Publishing
Publisher Date	2015-06-03
Publisher Place	Moscow
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Theoretical Computer Science Computer Networks and Communications Control and Systems Engineering Information Systems Computer Vision and Pattern Recognition Software

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Inference methods for systems with many fuzzy inputs