Results 221 to 230 of about 157,297 (256)

The Study of Max-Min Composition in Fuzzy Relation

Patan Prospective Journal, 2023
One of the foundational concepts in both pure and applied mathematics is the notion of relations. Fuzzy relations extend this concept much like fuzzy sets generalize the fundamental idea of sets. This study provides a comprehensive overview of operations, compositions, and the various types inherent in fuzzy relations.
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Materialized View Creation by Fuzzy MAX-MIN Composition

2021
View materialization technique is considered to be an important aspect of research for relational model based data centric applications where the amount of data is moderately high. Different queries are required to be answered against the user generated requests from these data centric applications.
Partha Ghosh, Takaaki Goto, Soumya Sen
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Study of Dependability Evaluation for Multi‐hierarchical Systems Based on Max–Min Composition

Quality and Reliability Engineering International, 2012
This article presents the model for calculating the performance of dependability for complex technical systems. According to ISO‐IEC 300, dependability is an overall indicator for the quality of service and considers simultaneously reliability, maintainability, and maintenance support.
Milos Tanasijevic, Dejan Ivezic, Predrag D. Jovancic, Dobrivoje Catic, Dragan Zlatanovic   +4 more
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Fuzzy linear optimization in the presence of the fuzzy relation inequality constraints with max–min composition

Information Sciences, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Amin Ghodousian, Esmaile Khorram
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Zadeh max–min composition fuzzy rule for dominated pixel values in iris localization

Soft Computing, 2018
Iris detection fails at the iris localization stage pulling out of the sub-image from the original image; the objective of this paper is to realize the narrative approach for iris localization and to solve the localization problem in an image using a dominant localization max–min algorithm which increases accuracy and reduces the search time.
S. G. Gino Sophia, Victor Ceronmani Sharmila   +1 more
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NEW RESOLUTION OF FINITE FUZZY RELATION EQUATIONS WITH MAX-MIN COMPOSITION

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2008
The work considers the problem of solvability of a fuzzy relation equation with max-min composition. It presents the necessary and sufficient conditions for the existence of solutions, then derives a fast algorithm for finding all minimal solutions. The results are compared with those of previous publications regarding this subject.
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A ZADEH’S MAX-MIN COMPOSITION OPERATOR FOR TWO 2-DIMENSIONAL QUADRATIC FUZZY NUMBERS

Far East Journal of Mathematical Sciences (FJMS), 2017
Summary: Generating triangular fuzzy numbers on \(\mathbb R\) to \(\mathbb R^2\) we define parametric operations between two regions valued a-cuts and obtain the parametric operations for two triangular fuzzy numbers defined on \(\mathbb R^2\). The results for the parametric operations are the generalization of Zadeh's extended algebraic operations ...
Kang, Chul, Yun, Yong Sik
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Sets of solution-set-invariant coefficient matrices of fuzzy relation equations with max-min composition

Journal of Intelligent & Fuzzy Systems, 2018
This paper describes a set of solution-set-invariant coefficient matrices of the fuzzy relation equation with max-min composition A  ⊙  x  =  b or
Xue-ping Wang 0001, Lu-juan Liu, Xiaohong Zhang 0001   +2 more
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A Zadeh ^′ s max-min composition operator for 3-dimensional triangular fuzzy number

Journal of Intelligent & Fuzzy Systems, 2020
We generalized triangular fuzzy numbers from ℝ to
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Fuzzy Max-Min Composition in Quality Specifications of Multi-Agent System

INTERNATIONAL JOURNAL OF COMPUTING ALGORITHM, 2014
In this paper a new technique named Fuzzy Max- Min Composition is used to obtain prioritization of quality specifications that assist quality engineer in achieving the desired level of quality for Multi- agent systems. Intuitionistic fuzzy Set has been used to capture the uncertainties associated with stakeholder's recommendation.
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