Add to ORKGThis paper presents a fuzzy classifier with the fuzzy rules base extracted from data and optimised by the Particle Swarm Optimisation algorithm. The paper discusses the fuzzy model and its applications. The results of the experimental testing show high accuracy of classification and efficiency of the proposed method
This paper presents a novel boosting algorithm for genetic learning of fuzzy classification rules. T...
This paper present a novel method based on multi-objective genetic algorithm to construct fuzzy clas...
This paper presents an approach to integrate multiple fuzzy knowledge bases for increasing the accur...
This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle ...
The most challenging problem in the design of fuzzy rule-based classification systems is the constru...
The use of fuzzy quantifiers to modify the fuzzy linguistic terms in fuzzy models helps build fuzzy ...
A new method for color image segmentation using fuzzy logic is proposed in this paper. Our aim here ...
classifier) is proposed in this paper. This classifier is described for finding the decision hyperpl...
Fuzzy segmentation is an effective way of segmenting out objects in images containing both random no...
Fuzzy rule-based classification systems have been used extensively in data mining. This paper propos...
In this paper, we propose a particle swarm optimization method incorporating quantum qubit operation...
The most challenging problem in developing fuzzy rule-based classification systems is the constructi...
The study is concerned with data and feature reduction in fuzzy modeling. As these reduction activit...
Abstract – In this paper we are dealing with the construction of a fuzzy rule based classifier. A th...
This paper proposes a new approach for automating the structure and parameter learning of fuzzy syst...
This paper presents a novel boosting algorithm for genetic learning of fuzzy classification rules. T...
This paper present a novel method based on multi-objective genetic algorithm to construct fuzzy clas...
This paper presents an approach to integrate multiple fuzzy knowledge bases for increasing the accur...
This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle ...
The most challenging problem in the design of fuzzy rule-based classification systems is the constru...
The use of fuzzy quantifiers to modify the fuzzy linguistic terms in fuzzy models helps build fuzzy ...
A new method for color image segmentation using fuzzy logic is proposed in this paper. Our aim here ...
classifier) is proposed in this paper. This classifier is described for finding the decision hyperpl...
Fuzzy segmentation is an effective way of segmenting out objects in images containing both random no...
Fuzzy rule-based classification systems have been used extensively in data mining. This paper propos...
In this paper, we propose a particle swarm optimization method incorporating quantum qubit operation...
The most challenging problem in developing fuzzy rule-based classification systems is the constructi...
The study is concerned with data and feature reduction in fuzzy modeling. As these reduction activit...
Abstract – In this paper we are dealing with the construction of a fuzzy rule based classifier. A th...
This paper proposes a new approach for automating the structure and parameter learning of fuzzy syst...
This paper presents a novel boosting algorithm for genetic learning of fuzzy classification rules. T...
This paper present a novel method based on multi-objective genetic algorithm to construct fuzzy clas...
This paper presents an approach to integrate multiple fuzzy knowledge bases for increasing the accur...