The slime mould algorithm (SMA) is a population-based optimization algorithm that mimics
the foraging behavior of slime moulds with a simple structure and few hyperparameters …

Abst The advent of Big Data has rendered Machine Learning tasks more intricate as they
frequently involve higher-dimensional data. Feature Selection (FS) methods can abate the …

To improve the detection of COVID-19, this paper researches and proposes an effective
swarm intelligence algorithm-driven multi-threshold image segmentation (MTIS) method …

Harris hawks optimization (HHO) has been accepted as one of the well-established swarm-
based methods in the community of optimization and machine learning that primarily works …

Functional connectivity (FC) derived from resting-state fMRI (rs-fMRI) is a primary approach
for identifying brain diseases, but it is limited to capturing the pairwise correlation between …

Large and medium-sized general hospitals have adopted artificial intelligence big data
systems to optimize the management of medical resources to improve the quality of hospital …

Recently, swarm intelligence algorithms have received much attention because of their
flexibility for solving complex problems in the real world. Recently, a new algorithm called …

The slime mould algorithm (SMA) is a population-based swarm intelligence optimization
algorithm that simulates the oscillatory foraging behavior of slime moulds. To overcome its …

The evaluation of coronary morphology provides important guidance for the treatment of
coronary heart disease (CHD). A chaotic Gaussian mutation antlion optimizer algorithm …

The sine cosine algorithm (SCA) is a metaheuristic algorithm proposed in recent years that
does not resort to nature-related metaphors but explores and exploits the search space with …