Add to ORKGIn this paper, a new fuzzy clustering algorithm that uses cellular learning automata based evolutionary computing (CLA-EC) is proposed. The CLA-EC is a model obtained by combining the concepts of cellular learning automata and evolutionary algorithms. The CLA-EC is used to search for cluster centers in such a way that minimizes the clustering criterion. The simulation results indicate that the proposed algorithm produces clusters with acceptable quality with respect to clustering criterion and provides a performance that is superior to that of the C-means algorithm. 1
This paper introduces a hybrid genetic algorithm that uses fuzzy c-means clustering technique as a m...
Clustering algorithms are widely used in pattern recognition and data mining applications. Due to th...
Clustering (or cluster analysis) aims toorganize a collection of data items into clusters,such that ...
101 p.Clustering represents a core research area of machine learning. It has been widely used in dat...
In this paper, an evolutionary programming-based clustering algorithm is proposed. The algorithm eff...
Wireless sensor networks have attracted attention of researchers considering their abundant applicat...
This paper introduces an evolutionary approach to automatically determine the optimal number and loc...
A fuzzy version of an Evolutionary Algorithm for Clustering (EAC) proposed in, previous work is intr...
This paper presents a survey of evolutionary algorithms designed for clustering tasks. It tries to r...
This paper tackles the problem of showing that evolutionary algorithms for fuzzy clustering can be m...
In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data ...
the original method of fuzzy clustering using genetic algorithm is proposed. The chromosomes of the...
This paper presents a fuzzy clustering method based on multiobjective genetic algorithm. The ADNSGA2...
AbstractWhile clustering the data using fuzzy c-means (FCM) and hard c-means (HCM), the sensitivity ...
In data analysis and data mining technique fields, one of the most widely used methods is clustering...
This paper introduces a hybrid genetic algorithm that uses fuzzy c-means clustering technique as a m...
Clustering algorithms are widely used in pattern recognition and data mining applications. Due to th...
Clustering (or cluster analysis) aims toorganize a collection of data items into clusters,such that ...
101 p.Clustering represents a core research area of machine learning. It has been widely used in dat...
In this paper, an evolutionary programming-based clustering algorithm is proposed. The algorithm eff...
Wireless sensor networks have attracted attention of researchers considering their abundant applicat...
This paper introduces an evolutionary approach to automatically determine the optimal number and loc...
A fuzzy version of an Evolutionary Algorithm for Clustering (EAC) proposed in, previous work is intr...
This paper presents a survey of evolutionary algorithms designed for clustering tasks. It tries to r...
This paper tackles the problem of showing that evolutionary algorithms for fuzzy clustering can be m...
In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data ...
the original method of fuzzy clustering using genetic algorithm is proposed. The chromosomes of the...
This paper presents a fuzzy clustering method based on multiobjective genetic algorithm. The ADNSGA2...
AbstractWhile clustering the data using fuzzy c-means (FCM) and hard c-means (HCM), the sensitivity ...
In data analysis and data mining technique fields, one of the most widely used methods is clustering...
This paper introduces a hybrid genetic algorithm that uses fuzzy c-means clustering technique as a m...
Clustering algorithms are widely used in pattern recognition and data mining applications. Due to th...
Clustering (or cluster analysis) aims toorganize a collection of data items into clusters,such that ...