Swarm Intelligence-Based PID Tuning for Drone Control in Photovoltaic Panel Monitoring using Fire Hawk Algorithm DOI
José Fonseca,

Lorenzo Valente,

Paulo Jefferson Dias de Oliveira Evald

et al.

Published: Oct. 20, 2024

Language: Английский

Flood algorithm (FLA): an efficient inspired meta-heuristic for engineering optimization DOI
Mojtaba Ghasemi, Keyvan Golalipour, Mohsen Zare

et al.

The Journal of Supercomputing, Journal Year: 2024, Volume and Issue: 80(15), P. 22913 - 23017

Published: July 1, 2024

Language: Английский

Citations

34
Application of the 2-archive multi-objective cuckoo search algorithm for structure optimization DOI Creative Commons
Ghanshyam G. Tejani, Nikunj Mashru, Pinank Patel

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 30, 2024

The study suggests a better multi-objective optimization method called 2-Archive Multi-Objective Cuckoo Search (MOCS2arc). It is then used to improve eight classical truss structures and six ZDT test functions. aims minimize both mass compliance simultaneously. MOCS2arc an advanced version of the traditional (MOCS) algorithm, enhanced through dual archive strategy that significantly improves solution diversity performance. To evaluate effectiveness MOCS2arc, we conducted extensive comparisons with several established algorithms: MOSCA, MODA, MOWHO, MOMFO, MOMPA, NSGA-II, DEMO, MOCS. Such comparison has been made various performance metrics compare benchmark efficacy proposed algorithm. These comprehensively assess algorithms' abilities generate diverse optimal solutions. statistical results demonstrate superior evidenced by Additionally, Friedman's & Wilcoxon's corroborate finding consistently delivers compared others. show highly effective improved algorithm for structure optimization, offering significant promising improvements over existing methods.

Language: Английский

Citations

11
The Pine Cone Optimization Algorithm (PCOA) DOI Creative Commons
Mahdi Valikhan Anaraki, Saeed Farzin

Biomimetics, Journal Year: 2024, Volume and Issue: 9(2), P. 91 - 91

Published: Feb. 1, 2024

The present study introduces a novel nature-inspired optimizer called the Pine Cone Optimization algorithm (PCOA) for solving science and engineering problems. PCOA is designed based on different mechanisms of pine tree reproduction, including pollination cone dispersal by gravity animals. It employs new powerful operators to simulate mentioned mechanisms. performance analyzed using classic benchmark functions, CEC017 CEC2019 as mathematical problems CEC2006 CEC2011 design In terms accuracy, results show superiority well-known algorithms (PSO, DE, WOA) (AVOA, RW_GWO, HHO, GBO). are competitive with state-of-the-art (LSHADE EBOwithCMAR). convergence speed time complexity, reasonable. According Friedman test, PCOA’s rank 1.68 9.42 percent better than EBOwithCMAR (second-best algorithm) LSHADE (third-best algorithm), respectively. authors recommend science, engineering, industrial societies complex optimization

Language: Английский

Citations

7
Hierarchical RIME algorithm with multiple search preferences for extreme learning machine training DOI Creative Commons
Rui Zhong, Chao Zhang, Jun Yu

et al.

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 110, P. 77 - 98

Published: Oct. 7, 2024

Language: Английский

Citations

7
Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration Versus Algorithmic Behavior, Critical Analysis Recommendations DOI
Daniel Molina, Javier Poyatos, Javier Del Ser

et al.

Cognitive Computation, Journal Year: 2020, Volume and Issue: 12(5), P. 897 - 939

Published: July 5, 2020

Language: Английский

Citations

41
An innovative complex-valued encoding black-winged kite algorithm for global optimization DOI Creative Commons

Chengtao Du,

Jinzhong Zhang, Jie Fang

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 6, 2025

Language: Английский

Citations

0
Multi-strategy fusion pelican optimization algorithm and logic operation ensemble of transfer functions for high-dimensional feature selection problems DOI

Hao-Ming Song,

Jie-Sheng Wang,

Jia-Ning Hou

et al.

International Journal of Machine Learning and Cybernetics, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 17, 2025

Language: Английский

Citations

0
Application of Metaheuristic Algorithms with Supervised Machine Learning for Accurate Power Consumption Prediction DOI
Mengxia Wang, Chaoyang Zhu, Yunxiang Zhang

et al.

Cognitive Computation, Journal Year: 2025, Volume and Issue: 17(1)

Published: Jan. 30, 2025

Language: Английский

Citations

0
An efficient prediction of punching shear strength in reinforced concrete slabs through boosting methods and metaheuristic algorithms DOI

Erfan Khajavi,

Amir Reza Taghavi Khanghah,

Ali Javadzade Khiavi

et al.

Structures, Journal Year: 2025, Volume and Issue: 74, P. 108519 - 108519

Published: Feb. 24, 2025

Language: Английский

Citations

0
Dynamic time-varying transfer function for cancer gene expression data feature selection problem DOI Creative Commons

Hao-Ming Song,

Yucai Wang, Jie-Sheng Wang

et al.

Journal Of Big Data, Journal Year: 2025, Volume and Issue: 12(1)

Published: March 1, 2025

Language: Английский

Citations

0