Application of swarm intelligence optimization algorithms in image processing: A comprehensive review of analysis, synthesis, and optimization
M Xu, L Cao, D Lu, Z Hu, Y Yue - Biomimetics, 2023 - mdpi.com
Image processing technology has always been a hot and difficult topic in the field of artificial
intelligence. With the rise and development of machine learning and deep learning …
intelligence. With the rise and development of machine learning and deep learning …
Interval forecasting for urban water demand using PSO optimized KDE distribution and LSTM neural networks
B Du, S Huang, J Guo, H Tang, L Wang, S Zhou - Applied Soft Computing, 2022 - Elsevier
The current literature on water demand forecasting mostly focuses on giving accurate point
predictions of water demand. However, the water demand point forecasting will encounter …
predictions of water demand. However, the water demand point forecasting will encounter …
Bioinspired algorithms for multiple sequence alignment: a systematic review and roadmap
Multiple Sequence Alignment (MSA) plays a pivotal role in bioinformatics, facilitating various
critical biological analyses, including the prediction of unknown protein structures and …
critical biological analyses, including the prediction of unknown protein structures and …
Improved manta ray foraging optimization for multi-level thresholding using COVID-19 CT images
EH Houssein, MM Emam, AA Ali - Neural Computing and Applications, 2021 - Springer
Abstract Coronavirus disease 2019 (COVID-19) is pervasive worldwide, posing a high risk to
people's safety and health. Many algorithms were developed to identify COVID-19. One way …
people's safety and health. Many algorithms were developed to identify COVID-19. One way …
A novel improved whale optimization algorithm to solve numerical optimization and real-world applications
Whale optimization algorithm (WOA) has been developed based on the hunting behavior of
humpback whales. Though it has a considerable convergence speed, WOA suffers from …
humpback whales. Though it has a considerable convergence speed, WOA suffers from …
CGFFCM: Cluster-weight and Group-local Feature-weight learning in Fuzzy C-Means clustering algorithm for color image segmentation
The fuzzy c-means (FCM) algorithm is a popular method for data clustering and image
segmentation. However, the main problem of this algorithm is that it is very sensitive to the …
segmentation. However, the main problem of this algorithm is that it is very sensitive to the …
An efficient multi-thresholding based COVID-19 CT images segmentation approach using an improved equilibrium optimizer
Optimization is the process of searching for the optimal (best-so-far) solution among a wide
range of solutions. Besides, in the last two decades, a family of algorithms known as …
range of solutions. Besides, in the last two decades, a family of algorithms known as …
Intelligent fault diagnosis among different rotating machines using novel stacked transfer auto-encoder optimized by PSO
S Haidong, D Ziyang, C Junsheng, J Hongkai - ISA transactions, 2020 - Elsevier
Intelligent fault diagnosis techniques cross rotating machines have great significances in
theory and engineering For this purpose, this paper presents a novel method using novel …
theory and engineering For this purpose, this paper presents a novel method using novel …
A strategy learning framework for particle swarm optimization algorithm
HQ Xu, S Gu, YC Fan, XS Li, YF Zhao, J Zhao… - Information …, 2023 - Elsevier
Many variants with various strategies have been proposed to improve the efficiency of
Particle Swarm Optimization (PSO) algorithm. These strategies are a precious resource …
Particle Swarm Optimization (PSO) algorithm. These strategies are a precious resource …
HWOA: A hybrid whale optimization algorithm with a novel local minima avoidance method for multi-level thresholding color image segmentation
Traditional methods to address color image segmentation work efficiently for bi-level
thresholding. However, for multi-level thresholding, traditional methods suffer from time …
thresholding. However, for multi-level thresholding, traditional methods suffer from time …