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 …

In this article, we propose a lightweight and competitively accurate heart rhythm abnormality
classification model based on classical convolutional neural networks in deep neural …

This paper proposes an efficient optimization algorithm based on the physical phenomenon
of rime-ice, called the RIME. The RIME algorithm implements the exploration and …

In order to effectively solve multi-objective optimization problems (MOPs) and fully balance
uniformity and convergence, a multi-strategy competitive-cooperative co-evolutionary …

The population structure of differential evolution (DE) algorithm cannot maintain the diversity
of the population to the greatest extent and help the population avoid to fall into the local …

Introduction The main feature selection methods include filter, wrapper-based, and
embedded methods. Because of its characteristics, the wrapper method must include a …

Continuous ant colony optimization was a population-based heuristic search algorithm
inspired by the pathfinding behavior of ant colonies with a simple structure and few control …

Abstract Feature Subset Selection (FSS) is an NP-hard problem to remove redundant and
irrelevant features particularly from medical data, and it can be effectively addressed by …

Lupus Nephritis (LN) is a significant risk factor for morbidity and mortality in systemic lupus
erythematosus, and nephropathology is still the gold standard for diagnosing LN. To assist …

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 …