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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.


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Journal ArticleDOI
TL;DR: A method of fuzzy rule weight specification using Receiver Operating Characteristic (ROC) analysis is proposed, using 2-class ROC analysis, to specify the weight of a fuzzy rule, using the threshold that the rule achieves its maximum accuracy.

56 citations

Journal ArticleDOI
TL;DR: The results of the paper allow us to associate a vague group to every fuzzy subgroup μ in such a way that it can be interpreted as the fuzzy quotient group X/μ.

56 citations

Journal ArticleDOI
01 Aug 2011
TL;DR: A new fuzzy model is presented to simulate and synchronize two totally different and complicated chaotic systems, namely, 1) quantum cellular neural networks nanosystem (Quantum-CNN system) and 2) Qi system.
Abstract: In this paper, a new fuzzy model is presented to simulate and synchronize two totally different and complicated chaotic systems, namely, 1) quantum cellular neural networks nanosystem (Quantum-CNN system) and 2) Qi system. Through the new fuzzy model, the following three main advantages can be obtained: 1) only two linear subsystems are needed; 2) the numbers of fuzzy rules can be reduced from 2 N to 2 ×N (comparing with the Takagi-Sugeno fuzzy model), where N is the number of nonlinear terms; 3) fuzzy synchronization of two different chaotic systems with different numbers of nonlinear terms can be achieved with only two sets of gain K. There are two examples in numerical simulation results to show the effectiveness and feasibility of our new model.

56 citations

Journal ArticleDOI
TL;DR: This dissertation presents an efficient approach that combines fuzzy logic and neural networks to capture these two important features required for an intelligent control system and indicates that fuzzy logicand neural networks are complementary and their combination is ideal to achieve the goal of intelligent control.
Abstract: This article proposes a design of adaptive fuzzy logic based control systems FLCSs with neural networks. A detailed discussion of effects of different reasoning methods on fuzzy controls is given and used to illustrate the need for an adaptive implementation of fuzzy controls. The procedure of decision-making of a FLCS leads to a neuro-fuzzy network consisting of three types of subnets for pattern recognition, fuzzy reasoning, and control synthesis, respectively. The unique knowledge structure embedded in this structured network enables it to carry out adaptive changes of fuzzy reasoning methods and membership functions for both input signal patterns and output control actions, and then recover these changes individually and completely later from its sub nets. Gradient methods for optimization have been used to derive off-line training rules and on-line learning algorithms for the structured neuro-fuzzy network. Issues related to rule modification and generation for an FLCS are addressed based on its network implementation.

56 citations

Proceedings ArticleDOI
21 Nov 2011
TL;DR: The ability of the genetic programming to evolve useful fuzzy classifiers is demonstrated on two use cases in which faulty products in a product processing plant and intrusions in a computer network are demonstrated.
Abstract: Fuzzy sets and fuzzy logic can be used for efficient data classification by fuzzy rules and fuzzy classifiers. This paper presents an application of genetic programming to the evolution of fuzzy classifiers based on extended Boolean queries. Extended Boolean queries are well known concept in the area of fuzzy information retrieval. An extended Boolean query represents a complex soft search expression that defines a fuzzy set on the collection of searched documents. We interpret the data mining task as a fuzzy information retrieval problem and we apply a proven method for query induction from data to find useful fuzzy classifiers. The ability of the genetic programming to evolve useful fuzzy classifiers is demonstrated on two use cases in which we detect faulty products in a product processing plant and discover intrusions in a computer network.

56 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20238
202216
20212
20201
20193
201825