Clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. K-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. In recent years, several algorithms are provided based on evolutionary algorithms for cluster...

Due to the extensive use of composites in various industries and the fact that defects reduce ultimate strength and efficiency during operation, detection of failures in composite parts is very important. The aim of this paper is to use Acoustic Emission (AE) non-destructive method in four-point bending test of carbon/epoxy composite to analyze and examine the failure mechanisms. This method is...

clustering is a widespread data analysis and data mining technique in many fields of study such as engineering, medicine, biology and the like. the aim of clustering is to collect data points. in this paper, a cultural algorithm (ca) is presented to optimize partition with n objects into k clusters. the ca is one of the effective methods for searching into the problem space in order to find a n...

Data clustering is a process of arranging similar data into groups. A clustering algorithm partitions a data set into several groups such that the similarity within a group is better than among groups. In this paper a hybrid clustering algorithm based on K-mean and K-harmonic mean (KHM) is described. The proposed algorithm is tested on five different datasets. The research is focused on fast an...

identifying clusters or clustering is an important aspect of data analysis. it is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. it is a main task of exploratory data mining, and a common technique for statistical data analysis this paper proposed an improved version of k-means algorithm, namely persistent k...

The accurate localization of S1 and S2 is essential for heart sound segmentation classification. However, current direct algorithms have poor noise immunity low accuracy. Therefore, this paper proposes a new optimal algorithm based on K-means clustering Haar wavelet transform. includes three parts. Firstly, method uses the Viola integral Shannon’s energy-based to extract function envelope energ...

Identifying clusters or clustering is an important aspect of data analysis. It is the task of grouping a set of objects in such a way those objects in the same group/cluster are more similar in some sense or another. It is a main task of exploratory data mining, and a common technique for statistical data analysis This paper proposed an improved version of K-Means algorithm, namely Persistent K...