Partitional data clustering with K-means algorithm is the dividing of objects into smaller and
disjoint groups that has the most similarity with objects in a group and most dissimilarity from …

The fuzzy k-modes (FKM) is a popular method for clustering categorical data. However, the
main problem of this algorithm is that it is very sensitive to the initialization of primary …

This paper addresses Acoustic Emission (AE) from Computer Numerical Control (CNC)
machining operations. Experimental measurements are performed on the CNC lathe …

Recently, various meta-heuristic algorithms have been considered to allocate the data into
different clusters based on similar information. These algorithms have obtained state of the …

Clustering arranges the data objects into clusters and similar data objects put into same
cluster. There is not a single algorithm that can work effectively with all types of clustering …

The clustering technique, which is widely employed for data analysis and data mining,
represents the way of gathering similar objects or data with each other according to similar …

To improve the precision, accuracy, and speed of the particle swarm optimization (PSO)
algorithm, the influence of the function concavity of the inertia weight reduction strategy on …

The clustering technique, which is widely employed for data analysis and data mining,
represents the way of gathering similar objects or data with each other according to similar …