Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms
in the literature. Although the original PSO has shown good optimization performance, it still …

Data clustering is one of the most popular techniques in data mining. It is a process of
partitioning an unlabeled dataset into groups, where each group contains objects which are …

Determining customer satisfaction elements in retailing after-sales services have been well
explored; however, the increasing competition in this area demands the investigation of …

The exponential growth in the number of flash flood events is a global threat, and detecting a
flood-prone area has also become a top priority. The flash flood-susceptibility map** can …

The fast-growing Internet results in massive amounts of text data. Due to the large volume of
the unstructured format of text data, extracting relevant information and its analysis becomes …

Nature has always been a source of inspiration. Over the last few decades, it has stimulated
many successful algorithms and computational tools for dealing with complex and …

In the mid 1990s two landmark metaheuristics have been proposed: Particle Swarm
Optimization and Differential Evolution. Their initial versions were very simple, but rapidly …

Krill herd (KH) is a stochastic nature-inspired optimization algorithm that has been
successfully used to solve numerous complex optimization problems. This paper proposed a …

This paper is inspired by traditional rural fishing methods and proposes a new metaheuristic
optimization algorithm based on human behavior: Catch Fish Optimization Algorithm …

In cluster analysis, a fundamental problem is to determine the best estimate of the number of
clusters; this is known as the automatic clustering problem. Because of lack of prior domain …