Particle swarm optimisation: a historical review up to the current developments
The Particle Swarm Optimisation (PSO) algorithm was inspired by the social and biological
behaviour of bird flocks searching for food sources. In this nature-based algorithm …
behaviour of bird flocks searching for food sources. In this nature-based algorithm …
A dynamic neighborhood-based switching particle swarm optimization algorithm
In this article, a dynamic-neighborhood-based switching PSO (DNSPSO) algorithm is
proposed, where a new velocity updating mechanism is designed to adjust the personal …
proposed, where a new velocity updating mechanism is designed to adjust the personal …
Reinforcement learning-based particle swarm optimization with neighborhood differential mutation strategy
The particle swarm optimization (PSO) algorithm has been one of the most effective methods
for solving various engineering optimization problems. Most existing PSO variants frequently …
for solving various engineering optimization problems. Most existing PSO variants frequently …
A ranking-system-based switching particle swarm optimizer with dynamic learning strategies
In this paper, a novel ranking-system-based switching particle swarm optimizer (RSPSO) is
proposed. In particular, according to a ranking system, the swarm is divided into elite and …
proposed. In particular, according to a ranking system, the swarm is divided into elite and …
A novel switching delayed PSO algorithm for estimating unknown parameters of lateral flow immunoassay
In this paper, the parameter identification problem of the lateral flow immunoassay (LFIA)
devices is investigated via a new switching delayed particle swarm optimization (SDPSO) …
devices is investigated via a new switching delayed particle swarm optimization (SDPSO) …
Path planning for intelligent robot based on switching local evolutionary PSO algorithm
N Zeng, H Zhang, Y Chen, B Chen, Y Liu - Assembly Automation, 2016 - emerald.com
Purpose This paper aims to present a novel particle swarm optimization (PSO) based on a
non-homogeneous Markov chain and differential evolution (DE) for path planning of …
non-homogeneous Markov chain and differential evolution (DE) for path planning of …
A novel switching local evolutionary PSO for quantitative analysis of lateral flow immunoassay
N Zeng, YS Hung, Y Li, M Du - Expert Systems with Applications, 2014 - Elsevier
This paper presents a novel particle swarm optimization (PSO) based on a non-
homogeneous Markov chain and differential evolution (DE) for quantification analysis of the …
homogeneous Markov chain and differential evolution (DE) for quantification analysis of the …
Recognition of brain cancer and cerebrospinal fluid due to the usage of different MRI image by utilizing support vector machine
S Saeed, A Abdullah - Bulletin of Electrical Engineering and Informatics, 2020 - beei.org
Medicinal images assume an important part in the diagnosis of tumors as well as
Cerebrospinal fluid (CSF) leak. Similarly, MRI could be the cutting-edge regenerative …
Cerebrospinal fluid (CSF) leak. Similarly, MRI could be the cutting-edge regenerative …
Statistical analysis of the pre-and post-surgery in the healthcare sector using high dimension segmentation
S Saeed, A Abdullah, NZ Jhanjhi, M Naqvi… - Machine Learning for …, 2020 - taylorfrancis.com
This chapter presents the achievements of the set objectives and the comparative
performance evaluations and simulation of experimental results. The researcher discusses …
performance evaluations and simulation of experimental results. The researcher discusses …
A review of deep learning architectures and their application
JA Mohd Kamarudin, A Abdullah… - Modeling, Design and …, 2017 - Springer
Deep Learning is a new era of machine learning research that are making major advances
in solving problem with powerful computational models. Currently, this new machine …
in solving problem with powerful computational models. Currently, this new machine …