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 …

Abstract The Artificial Bee Colony (ABC) technique is a highly effective method of
optimization inspired by the behavior of bees. Notably, the importance of the ABC algorithm …

The improvement of enterprise competitiveness depends on the ability to match segmented
customers in a competitive market. In this study, we propose a customer segmentation …

In this research, we propose two variants of the Firefly Algorithm (FA), namely inward
intensified exploration FA (IIEFA) and compound intensified exploration FA (CIEFA), for …

In this article, a new optimization technique known as Kho-Kho optimization (KKO) algorithm
is presented. This proposed technique is a population based meta-heuristic method which is …

Data clustering is one of the branches of unsupervised learning and it is a process whereby
the samples are divided into categories whose members are similar to each other. The K …

Intrusion detection maintains network security by detecting intrusion behaviors. There are
many clustering algorithms that can be used directly for intrusion detection. K-means is a …

Along with expansion in using of Internet and computer networks, the privacy, integrity, and
access to digital resources have been faced with permanent risks. Due to the unpredictable …

郊狼优化算法(Coyote optimization algorithm, COA) 是最近提出的一种新颖且具有较大应用
潜力的群智能优化算法, 具有独特的搜索机制和能较好解决全局优化问题等优势 …

Abstract Internet of Medical Things (IoMT) is a recently introduced paradigm which has
gained relevance as an emerging technology for widely connected and heterogeneous …