Advances in recent techniques for scientific data collection in the era of big data allow for the
systematic accumulation of large quantities of data at various data-capturing sites. Similarly …

K-means clustering algorithm is a partitional clustering algorithm that has been used widely
in many applications for traditional clustering due to its simplicity and low computational …

This paper introduces an innovative automatic K-means clustering algorithm, namely HGA-
FACO, which seamlessly integrates the noise algorithm, Genetic Algorithm (GA), Ant Colony …

Clustering is one of the data mining methods that partition large-sized data into subgroups
according to their similarities. K-means clustering algorithm works well in spherical or …

The proliferation of Internet of Things (IoT) systems and smart digital devices, has perceived
them targeted by network attacks. Botnets are vectors buttoned up which the attackers …

Clustering is a commonly used method for exploring and analysing data where the primary
objective is to categorise observations into similar clusters. In recent decades, several …

With the increasing number of samples, the manual clustering of COVID-19 and medical
disease data samples becomes time-consuming and requires highly skilled labour …

Deploying uncrewed aerial vehicles (UAVs) as aerial base stations (BSs) to assist terrestrial
connectivity has drawn significant attention in recent years. Alongside other UAV types …

Due to the advancements in the lifestyle, stress builds enormously among individuals. A few
recent studies have indicated that stress is a major contributor for infertility and subsequent …

Kmeans clustering algorithm is an iterative unsupervised learning algorithm that tries to
partition the given dataset into k pre-defined distinct non-overlap** clusters where each …