Eagle Strategy in Nature-Inspired Optimization: Theory, Analysis, Applications, and Comparative Study DOI
Krishna Gopal Dhal, Arunita Das, Buddhadev Sasmal

et al.

Archives of Computational Methods in Engineering, Journal Year: 2023, Volume and Issue: 31(3), P. 1213 - 1232

Published: Oct. 24, 2023

Language: Английский

Human-Inspired Optimization Algorithms: Theoretical Foundations, Algorithms, Open-Research Issues and Application for Multi-Level Thresholding DOI Open Access
Rebika Rai, Arunita Das, Swarnajit Ray

et al.

Archives of Computational Methods in Engineering, Journal Year: 2022, Volume and Issue: 29(7), P. 5313 - 5352

Published: June 7, 2022

Language: Английский

Citations

36

Lung X-Ray Image Segmentation Using Heuristic Red Fox Optimization Algorithm DOI Creative Commons
Antoni Jaszcz, Dawid Połap, Robertas Damaševičius

et al.

Scientific Programming, Journal Year: 2022, Volume and Issue: 2022, P. 1 - 8

Published: July 31, 2022

Medical image segmentation identifies an area that should be analyzed later in the processing process, such as for disease recognition and classification. As search is reduced, this action allows faster computation analysis. We propose use of a heuristic red fox optimization algorithm (RFOA) medical paper. The heuristics’ operation was adapted to analysis two-dimensional images, with focus on equation modification novel fitness function. proposed solution analyzes by converting selected pixels one two color variants, black or white, based threshold value used. Their number counted, allowing chosen threshold. result, results automatic selection parameter. Our method new function adjustment RFOA used publicly available database lung X-ray images evaluation, results, accuracy performed, well discussion benefits drawbacks presented.

Language: Английский

Citations

35

Archimedes Optimizer: Theory, Analysis, Improvements, and Applications DOI Open Access
Krishna Gopal Dhal, Swarnajit Ray, Rebika Rai

et al.

Archives of Computational Methods in Engineering, Journal Year: 2023, Volume and Issue: 30(4), P. 2543 - 2578

Published: Jan. 5, 2023

Language: Английский

Citations

20

Recent Developments in Equilibrium Optimizer Algorithm: Its Variants and Applications DOI Open Access
Rebika Rai, Krishna Gopal Dhal

Archives of Computational Methods in Engineering, Journal Year: 2023, Volume and Issue: 30(6), P. 3791 - 3844

Published: April 12, 2023

Language: Английский

Citations

20

Multi-threshold segmentation of breast cancer images based on improved dandelion optimization algorithm DOI

Zhenghong Wang,

Fanhua Yu, Dan Wang

et al.

The Journal of Supercomputing, Journal Year: 2023, Volume and Issue: 80(3), P. 3849 - 3874

Published: Sept. 7, 2023

Language: Английский

Citations

15

Fundus image segmentation based on random collision whale optimization algorithm DOI
Donglin Zhu, Xingyun Zhu,

Yuemai Zhang

et al.

Journal of Computational Science, Journal Year: 2024, Volume and Issue: 80, P. 102323 - 102323

Published: May 24, 2024

Language: Английский

Citations

5

XECryptoGA: a metaheuristic algorithm-based block cipher to enhance the security goals DOI
Md Saquib Jawed, Mohammad Sajid

Evolving Systems, Journal Year: 2022, Volume and Issue: 14(5), P. 749 - 770

Published: Sept. 21, 2022

Language: Английский

Citations

19

Elite levy spreading differential evolution via ABC shrink-wrap for multi-threshold segmentation of breast cancer images DOI
Jie Xing,

Xinsen Zhou,

Hanli Zhao

et al.

Biomedical Signal Processing and Control, Journal Year: 2023, Volume and Issue: 82, P. 104592 - 104592

Published: Jan. 18, 2023

Language: Английский

Citations

12

Advancements in Q‐learning meta‐heuristic optimization algorithms: A survey DOI
Yang Yang, Yuchao Gao, Zhe Ding

et al.

Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, Journal Year: 2024, Volume and Issue: 14(6)

Published: Aug. 18, 2024

Abstract This paper reviews the integration of Q‐learning with meta‐heuristic algorithms (QLMA) over last 20 years, highlighting its success in solving complex optimization problems. We focus on key aspects QLMA, including parameter adaptation, operator selection, and balancing global exploration local exploitation. QLMA has become a leading solution industries like energy, power systems, engineering, addressing range mathematical challenges. Looking forward, we suggest further integration, transfer learning strategies, techniques to reduce state space. article is categorized under: Technologies > Computational Intelligence Artificial

Language: Английский

Citations

4

Optimizing Multilevel Image Segmentation with a Modified New Caledonian Crow Learning Algorithm DOI Creative Commons

Osama Moh'dAlia

Systems and Soft Computing, Journal Year: 2025, Volume and Issue: unknown, P. 200206 - 200206

Published: Feb. 1, 2025

Language: Английский

Citations

0