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Clustering techniques have received attention in many fields of study such as engineering, medicine, biology and data mining. The aim of clustering is to collect data points. The K-means algorithm is one of the most common techniques used for clustering. However, the results of K-means depend on the initial state and converge to local optima. In order to overcome local optima obstacles, a lot of studies...
. Clustering is a process for partitioning datasets. This technique is very useful for optimum solution. k-means is one of the simplest and the most famous methods that is based on square error criterion. This algorithm depends on initial states and converges to local optima. Some recent researches show that k-means algorithm has been successfully applied to combinatorial optimization problems for...
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