A survey on particle swarm optimization with emphasis on engineering and network applications
Swarm intelligence is a kind of artificial intelligence that is based on the collective behavior
of the decentralized and self-organized systems. This work focuses on reviewing a heuristic …
of the decentralized and self-organized systems. This work focuses on reviewing a heuristic …
A survey on GPU-based implementation of swarm intelligence algorithms
Inspired by the collective behavior of natural swarm, swarm intelligence algorithms (SIAs)
have been developed and widely used for solving optimization problems. When applied to …
have been developed and widely used for solving optimization problems. When applied to …
Ensemble particle swarm optimizer
N Lynn, PN Suganthan - Applied Soft Computing, 2017 - Elsevier
Abstract According to the “No Free Lunch (NFL)” theorem, there is no single optimization
algorithm to solve every problem effectively and efficiently. Different algorithms possess …
algorithm to solve every problem effectively and efficiently. Different algorithms possess …
Particle swarm optimization for bandwidth determination and feature selection of kernel density estimation based classifiers in diagnosis of breast cancer
R Sheikhpour, MA Sarram, R Sheikhpour - Applied Soft Computing, 2016 - Elsevier
Abstract Machine learning techniques can be used in diagnosis of breast cancer to help
pathologists and physicians for decision making process. Kernel density estimation is a …
pathologists and physicians for decision making process. Kernel density estimation is a …
Generation-level parallelism for evolutionary computation: A pipeline-based parallel particle swarm optimization
Due to the population-based and iterative-based characteristics of evolutionary computation
(EC) algorithms, parallel techniques have been widely used to speed up the EC algorithms …
(EC) algorithms, parallel techniques have been widely used to speed up the EC algorithms …
An improved adaptive genetic algorithm based on DV-Hop for locating nodes in wireless sensor networks
A Ouyang, Y Lu, Y Liu, M Wu, X Peng - Neurocomputing, 2021 - Elsevier
The localization problem of unknown nodes in wireless sensor networks (WSN) has drawn
increasing scholarly attention along together the popularity of meta-heuristic algorithms. To …
increasing scholarly attention along together the popularity of meta-heuristic algorithms. To …
Parallel random matrix particle swarm optimization scheduling algorithms with budget constraints on cloud computing systems
X Tang, C Shi, T Deng, Z Wu, L Yang - Applied Soft Computing, 2021 - Elsevier
Nowadays, increasing number of Internet of Things and mobile Internet application services
are migrated to cloud computing systems. One of the most important cloud challenges for …
are migrated to cloud computing systems. One of the most important cloud challenges for …
Multi-modal prediction of breast cancer using particle swarm optimization with non-dominating sorting.
Cancer is enlisted as the second leading reason for death across the world wherein almost
one person out of six dies of cancer. Breast cancer is one of the most common forms of …
one person out of six dies of cancer. Breast cancer is one of the most common forms of …
Joint offloading and scheduling decisions for DAG applications in mobile edge computing
Mobile edge computing (MEC) is a promising technology to support computation-intensive
tasks for mobile devices which are usually associated with limited resources. Many …
tasks for mobile devices which are usually associated with limited resources. Many …
Cultural quantum-behaved particle swarm optimization for environmental/economic dispatch
In this paper, a novel CMOQPSO algorithm is proposed, in which cultural evolution
mechanism is introduced into quantum-behaved particle swarm optimization (QPSO) to …
mechanism is introduced into quantum-behaved particle swarm optimization (QPSO) to …