The set-based particle swarm optimisation algorithm is a swarm-based meta-heuristic that
has gained popularity in recent years. In contrast to the original particle swarm optimisation …

Automatic extracting of knowledge from massive data samples, ie, big data analytics (BDA),
has emerged as a vital task in almost all scientific research fields. The BDA problems are …

Liver-related diseases significantly contribute to global mortality rates. Accurate
segmentation of liver disease from CT scans is essential for early diagnosis and treatment …

An ontology typically provides a vocabulary describing a domain of interest and a
specification of the meaning of terms in that vocabulary. Depending on the precision of this …

Optimization techniques inspired by swarm intelligence have become increasingly popular
during the last decade. They are characterized by a decentralized way of working that …

The network intrusion detection techniques are important to prevent our systems and
networks from malicious behaviors. However, traditional network intrusion prevention such …

Particle swarm optimisation (PSO) is a biologically-inspired, population-based optimisation
technique that has been successfully applied to various problems in science and …

This article presented a parallel metaheuristic algorithm based on the Particle Swarm
Optimization (PSO) to solve global optimization problems. In recent years, many …

Increase of huge amount of data in every application demands an incremental learning
technique for data analysis. One of such data analysis task in dynamic environment is to …

The literature on protein function prediction is currently dominated by works aimed at
maximizing predictive accuracy, ignoring the important issues of validation and …