Cited by Self-adaptive moth flame optimizer combined with crossover operator and Fibonacci search strategy for COVID-19 CT image segmentation

A multi-factor combined traffic flow prediction model with secondary decomposition and improved entropy weight method DOI

Guohui Li, Haonan Deng, Hong Yang

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 255, P. 124424 - 124424

Published: June 18, 2024

Language: Английский

Citations

Dream Optimization Algorithm (DOA): A novel metaheuristic optimization algorithm inspired by human dreams and its applications to real-world engineering problems DOI

Yidong Lang,

Yuelin Gao

Computer Methods in Applied Mechanics and Engineering, Journal Year: 2025, Volume and Issue: 436, P. 117718 - 117718

Published: Jan. 9, 2025

Language: Английский

Citations

Lyrebird Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems DOI

Mohammad Dehghani,

Gulnara Bektemyssova,

Zeinab Montazeri

et al.

Biomimetics, Journal Year: 2023, Volume and Issue: 8(6), P. 507 - 507

Published: Oct. 23, 2023

In this paper, a new bio-inspired metaheuristic algorithm called the Lyrebird Optimization Algorithm (LOA) that imitates natural behavior of lyrebirds in wild is introduced. The fundamental inspiration LOA strategy when faced with danger. situation, scan their surroundings carefully, then either run away or hide somewhere, immobile. theory described and mathematically modeled two phases: (i) exploration based on simulation lyrebird escape (ii) exploitation hiding strategy. performance was evaluated optimization CEC 2017 test suite for problem dimensions equal to 10, 30, 50, 100. results show proposed approach has high ability terms exploration, exploitation, balancing them during search process problem-solving space. order evaluate capability dealing tasks, obtained from were compared twelve well-known algorithms. superior competitor algorithms by providing better most benchmark functions, achieving rank first best optimizer. A statistical analysis shows significant superiority comparison addition, efficiency handling real-world applications investigated through twenty-two constrained problems 2011 four engineering design problems. effective tasks while

Language: Английский

Citations

Chaotic Sand Cat Swarm Optimization DOI

Farzad Kiani, Sajjad Nematzadeh,

Fateme Aysin Anka

et al.

Mathematics, Journal Year: 2023, Volume and Issue: 11(10), P. 2340 - 2340

Published: May 17, 2023

In this study, a new hybrid metaheuristic algorithm named Chaotic Sand Cat Swarm Optimization (CSCSO) is proposed for constrained and complex optimization problems. This combines the features of recently introduced SCSO with concept chaos. The basic aim to integrate chaos feature non-recurring locations into SCSO’s core search process improve global performance convergence behavior. Thus, randomness in can be replaced by chaotic map due similar better statistical dynamic properties. addition these advantages, low consistency, local optimum trap, inefficiency search, population diversity issues are also provided. CSCSO, several maps implemented more efficient behavior exploration exploitation phases. Experiments conducted on wide variety well-known test functions increase reliability results, as well real-world was applied total 39 multidisciplinary It found 76.3% responses compared best-developed variant other chaotic-based metaheuristics tested. extensive experiment indicates that CSCSO excels providing acceptable results.

Language: Английский

Citations

Self-adaptive moth flame optimizer combined with crossover operator and Fibonacci search strategy for COVID-19 CT image segmentation DOI

Saroj Kumar Sahoo, Essam H. Houssein, M. Premkumar

et al.

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 227, P. 120367 - 120367

Published: May 6, 2023

Language: Английский

Citations