Over the ages, nature has constantly been a rich source of inspiration for science, with much
still to discover about and learn from. Swarm Intelligence (SI), a major branch of artificial …

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 …

Particle swarm optimization (PSO) is one of the most well-regard metaheuristics with
remarkable performance when solving diverse optimization problems. However, PSO faces …

The operations of metaheuristic optimization algorithms depend heavily on the setting of
control parameters. Therefore the addition of adaptive control parameter has been widely …

Particle swarm optimization (PSO) is a very simple and effective metaheuristic algorithm.
Search operators with similar behavior may lead to the loss of diversity in the search space …

All metaheuristic optimization algorithms require some initialization, and the initialization for
such optimizers is usually carried out randomly. However, initialization can have some …

Artificial neural networks (ANNs) have achieved great success in performing machine
learning tasks, including classification, regression, prediction, image processing, image …

The study shows that there are two main problems that affect the performance of fuzzy time
series (FTS) models, namely the selection of the universe of discourse and the …

In this research, we propose Particle Swarm Optimization (PSO)-enhanced ensemble deep
neural networks for optic disc (OD) segmentation using retinal images. An improved PSO …

Distribution systems continue to grow and becoming more complex with increasing
operational challenges such as protection miscoordination. Initially, conventional methods …