Online algorithms for clustering problems
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چکیده
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Solving Data Clustering Problems using Chaos Embedded Cat Swarm Optimization
In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...
متن کاملSolving Data Clustering Problems using Chaos Embedded Cat Swarm Optimization
In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...
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Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...
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So far, various optimization methods have been proposed, and swarm intelligence algorithms have gathered a lot of attention by academia. However, most of the recent optimization problems in the real world have a dynamic nature. Thus, an optimization algorithm is required to solve the problems in dynamic environments well. In this paper, a novel collective optimization algorithm, namely the Clus...
متن کاملAn Improved SSPCO Optimization Algorithm for Solve of the Clustering Problem
Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...
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Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible. In big data problems, clustering data is a useful tool for data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members ...
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