[HTML][HTML] Particle swarm optimization based on dimensional learning strategy

G Xu, Q Cui, X Shi, H Ge, ZH Zhan, HP Lee… - Swarm and Evolutionary …, 2019 - Elsevier
In traditional particle swarm optimization (PSO) algorithm, each particle updates its velocity
and position with a learning mechanism based on its personal best experience and the …

State of health estimation and remaining useful life prediction for lithium-ion batteries by improved particle swarm optimization-back propagation neural network

Y Ma, M Yao, H Liu, Z Tang - Journal of Energy Storage, 2022 - Elsevier
Abstract Accurate State of Health (SOH) estimation and Remaining Useful Life (RUL)
prediction play important roles in ensuring the safe operation of the batteries and minimizing …

Self-adaptive cost weights-based support vector machine cost-sensitive ensemble for imbalanced data classification

X Tao, Q Li, W Guo, C Ren, C Li, R Liu, J Zou - Information Sciences, 2019 - Elsevier
Imbalanced data classification poses a major challenge in data mining community. Although
standard support vector machine can generally show relatively robust performance in …

A parallel particle swarm optimization and enhanced sparrow search algorithm for unmanned aerial vehicle path planning

Z Wang, G Sun, K Zhou, L Zhu - Heliyon, 2023 - cell.com
Abstract Unmanned Aerial Vehicle (UAV) path planning is to plan an optimal path for its
flight in a specific environment. But it cannot get satisfactory results using ordinary …

A novel particle swarm optimization based on prey–predator relationship

H Zhang, M Yuan, Y Liang, Q Liao - Applied Soft Computing, 2018 - Elsevier
Particle swarm optimization (PSO) is a widely used nature-inspired optimization algorithm
based on population and has strong robustness and good global astringency. In the mid …

Develo** digital twin design for enhanced productivity of an automated anodizing industry and process prediction using hybrid deep neural network

V Kumar, V Manikandan, G Manavaalan… - … Applications of Artificial …, 2023 - Elsevier
Automation is beneficial when implemented in challenging environments requiring less
human effort or reducing human effort. Employee safety is a concern to increase productivity …

A modified multi swarm particle swarm optimization algorithm using an adaptive factor selection strategy

J Chrouta, F Farhani, A Zaafouri - Transactions of the …, 2021 - journals.sagepub.com
In the present study, we suggest a modified version of heterogeneous multi-swarm particle
swarm optimization (MSPSO) algorithm, that allows the amelioration of its performance by …

Multiple scale self-adaptive cooperation mutation strategy-based particle swarm optimization

X Tao, W Guo, Q Li, C Ren, R Liu - Applied Soft Computing, 2020 - Elsevier
Abstract Particle Swarm Optimization (PSO) algorithm has lately received great attention due
to its powerful search capacity and simplicity in implementation. However, previous studies …

Unsupervised and optimized thermal image quality enhancement and visual surveillance applications

T Trongtirakul, S Agaian - Signal Processing: Image Communication, 2022 - Elsevier
Thermal images suffer from low-luminance issues under specific conditions, such as heat
radiation, distance-to-radiated objects, reflection angles. Low-luminance thermal images …

Integrating a dimensional perturbation module into exponential distribution optimizer for solving optimization problems

P Shang, S Liu, H Ying, C Wang - Expert Systems with Applications, 2024 - Elsevier
Exponential distribution optimizer (EDO) is a recently proposed optimization technique that
is based on the exponential probability distribution model. As most swarm intelligence …