Topic
Fuzzy associative matrix
About: Fuzzy associative matrix is a research topic. Over the lifetime, 8027 publications have been published within this topic receiving 194790 citations.
Papers published on a yearly basis
Papers
More filters
01 Dec 2000
TL;DR: The work of Chen, Ke and Chang (1990) is extended to present a fuzzy backward reasoning algorithm for rule-based systems using fuzzy Petri nets, where the fuzzy production rules of a rule- based system are represented by fuzzyPetri nets.
Abstract: Chen, Ke and Chang (1990) have presented a fuzzy forward reasoning algorithm for rule-based systems using fuzzy Petri nets. In this paper, we extend the work of Chen, Ke and Chang (1990) to present a fuzzy backward reasoning algorithm for rule-based systems using fuzzy Petri nets, where the fuzzy production rules of a rule-based system are represented by fuzzy Petri nets. The system can perform fuzzy backward reasoning automatically to evaluate the degree of truth of any proposition specified by the user. The fuzzy backward reasoning capability allows the computers to perform reasoning in a more flexible manner and to think more like people.
71 citations
TL;DR: This paper illustrates some of the power of fuzzy logic through a simple control example that incorporates imprecision from measurement noise as well as from linguistic process descriptions to produce operational control systems.
Abstract: Fuzzy logic is a modeling method well suited for the control of complex and non-linear systems. This paper illustrates some of the power of fuzzy logic through a simple control example. For the analytical chemist, fuzzy logic incorporates imprecision from measurement noise as well as from linguistic process descriptions to produce operational control systems.
71 citations
TL;DR: A new multi-objective genetic algorithm is applied to solve the simple assembly line balancing problem of type 2 (SALBP-2) with fuzzy job processing times since uncertainty, variability, and imprecision are often occurred in real-world production systems.
Abstract: This paper presents a fuzzy extension of the simple assembly line balancing problem of type 2 (SALBP-2) with fuzzy job processing times since uncertainty, variability, and imprecision are often occurred in real-world production systems. The jobs processing times are formulated by triangular fuzzy membership functions. The total fuzzy cost function is formulated as the weighted-sum of two bi-criteria fuzzy objectives: (a) Minimizing the fuzzy cycle time and the fuzzy smoothness index of the workload of the line. (b) Minimizing the fuzzy cycle time of the line and the fuzzy balance delay time of the workstations. A new multi-objective genetic algorithm is applied to solve the problem whose performance is studied and discussed over known test problems taken from the open literature.
70 citations
23 Jul 2007
TL;DR: This work proposes a novel semantics combining the common product t-norm with the standard negation, and shows some interesting properties of the logic and proposes a reasoning algorithm based on a mixture of tableaux rules and the reduction to mixed integer quadratically constrained programming.
Abstract: Fuzzy description logics (fuzzy DLs) have been proposed as a language to describe structured knowledge with vague concepts. It is well known that the choice of the fuzzy operators may determine some logical properties. However, up to date the study of fuzzy DLs has been restricted to the Lukasiewicz logic and the "Zadeh semantics". In this work, we propose a novel semantics combining the common product t-norm with the standard negation. We show some interesting properties of the logic and propose a reasoning algorithm based on a mixture of tableaux rules and the reduction to mixed integer quadratically constrained programming.
70 citations
25 Aug 1993
TL;DR: All normal fuzzy sets may be realized as the interpolation of paradigmatic examples by a similarity relation and the class of fuzzy if-then rules that may be obtained by interpolation is a proper subset of the rules definable by disjunctive combination.
Abstract: A method for the construction of fuzzy concepts and fuzzy if-then rules based on similarity and paradigmatic examples is presented. It is shown that all normal fuzzy sets may be realized as the interpolation of paradigmatic examples by a similarity relation. The class of fuzzy if-then rules that may be obtained by interpolation, however, is a proper subset of the rules definable by disjunctive combination.
70 citations