An effective heart disease detection and severity level classification model using machine learning and hyperparameter optimization methods
Cardiovascular disease (CVD) is the leading cause of death worldwide. A Machine Learning
(ML) system can predict CVD in the early stages to mitigate mortality rates based on clinical …
(ML) system can predict CVD in the early stages to mitigate mortality rates based on clinical …
A gene selection algorithm for microarray cancer classification using an improved particle swarm optimization
Gene selection is an essential step for the classification of microarray cancer data. Gene
expression cancer data (deoxyribonucleic acid microarray] facilitates in computing the …
expression cancer data (deoxyribonucleic acid microarray] facilitates in computing the …
Golden jackal optimization with joint opposite selection: An enhanced nature-inspired optimization algorithm for solving optimization problems
This paper presents the logical relationships of Aristotle's square of opposition on four basic
categorial prepositions (ie, contrary, contradictory, subcontrary, and subaltern) of Joint …
categorial prepositions (ie, contrary, contradictory, subcontrary, and subaltern) of Joint …
Influence of the number of connections between particles in the performance of a multi-objective particle swarm optimizer
Abstract Particle Swarm Optimization (PSO) is a bio-inspired metaheuristic that operates on
a set of potential solutions (called particles). In PSO, each particle moves throughout the …
a set of potential solutions (called particles). In PSO, each particle moves throughout the …
An orthogonal learning bird swarm algorithm for optimal power flow problems
A dominant statistical method, in which the best combination of factors' levels are predicted
by analyzing a few representative combinations of factors' levels, named as orthogonal …
by analyzing a few representative combinations of factors' levels, named as orthogonal …
An ACO-based hyper-heuristic for sequencing many-objective evolutionary algorithms that consider different ways to incorporate the DM's preferences
Many-objective optimization is an area of interest common to researchers, professionals,
and practitioners because of its real-world implications. Preference incorporation into Multi …
and practitioners because of its real-world implications. Preference incorporation into Multi …
A many-objective particle swarm optimisation algorithm based on convergence assistant strategy
W Yang, L Chen, Y Li, F Abid - International Journal of Bio …, 2022 - inderscienceonline.com
The multi-objective particle swarm optimisation algorithm based on Pareto dominance also
has specific dilemmas when dealing with many-objective optimisation problems. For …
has specific dilemmas when dealing with many-objective optimisation problems. For …
GAPSO-Optimized fuzzy PID controller for electric-driven seeding
S Wang, B Zhao, S Yi, Z Zhou, X Zhao - Sensors, 2022 - mdpi.com
To improve the seeding motor control performance of electric-driven seeding (EDS), a
genetic particle swarm optimization (GAPSO)-optimized fuzzy PID control strategy for electric …
genetic particle swarm optimization (GAPSO)-optimized fuzzy PID control strategy for electric …
A powerful Peripheral Arterial Disease detection using machine learning-based severity level classification model and hyper parameter optimization methods
This study addresses the critical need for improved detection and assessment of Peripheral
Arterial Disease (PAD) using Artificial Intelligence (AI) algorithms, aiming to reduce global …
Arterial Disease (PAD) using Artificial Intelligence (AI) algorithms, aiming to reduce global …
Kinematic optimization of 6dof serial robot arms by bio-inspired algorithms
Robotic systems are essential to technological development in the industrial, medical, and
aerospace sectors. Nevertheless, their use in different applications requires that the robot …
aerospace sectors. Nevertheless, their use in different applications requires that the robot …