[Retracted] A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection
S Pervaiz, Z Ul-Qayyum, WH Bangyal… - … Methods in Medicine, 2021 - Wiley Online Library
Artificial Intelligence (AI) is the domain of computer science that focuses on the development
of machines that operate like humans. In the field of AI, medical disease detection is an …
of machines that operate like humans. In the field of AI, medical disease detection is an …
A comprehensive survey on particle swarm optimization algorithm and its applications
Y Zhang, S Wang, G Ji - Mathematical problems in engineering, 2015 - Wiley Online Library
Particle swarm optimization (PSO) is a heuristic global optimization method, proposed
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
Multiobjective evolutionary algorithms: A survey of the state of the art
A multiobjective optimization problem involves several conflicting objectives and has a set of
Pareto optimal solutions. By evolving a population of solutions, multiobjective evolutionary …
Pareto optimal solutions. By evolving a population of solutions, multiobjective evolutionary …
[PDF][PDF] A review of population-based meta-heuristic algorithms
Z Beheshti, SMH Shamsuddin - Int. j. adv. soft comput. appl, 2013 - academia.edu
Exact optimization algorithms are not able to provide an appropriate solution in solving
optimization problems with a high-dimensional search space. In these problems, the search …
optimization problems with a high-dimensional search space. In these problems, the search …
Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping
Using multiple ensemble learning techniques for improving the predictive accuracy of
landslide models is an active research area. In this study, we combined a radial basis …
landslide models is an active research area. In this study, we combined a radial basis …
Stacking-based multi-objective evolutionary ensemble framework for prediction of diabetes mellitus
Diabetes mellitus (DM) is a combination of metabolic disorders characterized by elevated
blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of …
blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of …
Performance evaluation of classification methods with PCA and PSO for diabetes
Diabetes has become one of the major health concerns for the modern day population. This
can be attributed to a number of factors such as unhealthy lifestyle, meager diet, genetics …
can be attributed to a number of factors such as unhealthy lifestyle, meager diet, genetics …
Neural network classifier optimization using differential evolution with global information and back propagation algorithm for clinical datasets
Abstract A Computer-Aided Diagnostic (CAD) system that uses Artificial Neural Network
(ANN) trained by drawing in the relative advantages of Differential Evolution (DE), Particle …
(ANN) trained by drawing in the relative advantages of Differential Evolution (DE), Particle …
Multi-objective optimization of seeding performance of a pneumatic precision seed metering device using integrated ANN-MOPSO approach
CM Pareek, VK Tewari, R Machavaram - Engineering Applications of …, 2023 - Elsevier
Uniform seed spacing within the row is the most desirable prerequisite for better crop yield.
The seeding uniformity of a pneumatic seed metering device is significantly affected by its …
The seeding uniformity of a pneumatic seed metering device is significantly affected by its …
Training radial basis function networks using biogeography-based optimizer
Training artificial neural networks is considered as one of the most challenging machine
learning problems. This is mainly due to the presence of a large number of solutions and …
learning problems. This is mainly due to the presence of a large number of solutions and …