Suppr超能文献

正弦余弦算法的全面综述:变体与应用

A comprehensive survey of sine cosine algorithm: variants and applications.

作者信息

Gabis Asma Benmessaoud, Meraihi Yassine, Mirjalili Seyedali, Ramdane-Cherif Amar

机构信息

Ecole nationale Supérieure d'Informatique, Laboratoire des Méthodes de Conception des Systèmes, BP 68M, 16309 Oued-Smar, Alger Algeria.

LIST Laboratory, University of M'Hamed Bougara Boumerdes, Avenue of Independence, 35000 Boumerdes, Algeria.

出版信息

Artif Intell Rev. 2021;54(7):5469-5540. doi: 10.1007/s10462-021-10026-y. Epub 2021 Jun 2.

Abstract

Sine Cosine Algorithm (SCA) is a recent meta-heuristic algorithm inspired by the proprieties of trigonometric sine and cosine functions. Since its introduction by Mirjalili in 2016, SCA has attracted great attention from researchers and has been widely used to solve different optimization problems in several fields. This attention is due to its reasonable execution time, good convergence acceleration rate, and high efficiency compared to several well-regarded optimization algorithms available in the literature. This paper presents a brief overview of the basic SCA and its variants divided into modified, multi-objective, and hybridized versions. Furthermore, the applications of SCA in several domains such as classification, image processing, robot path planning, scheduling, radial distribution networks, and other engineering problems are described. Finally, the paper recommended some potential future research directions for SCA.

摘要

正弦余弦算法(SCA)是一种最近受到三角函数正弦和余弦函数特性启发的元启发式算法。自2016年米尔贾利利提出以来,SCA已引起研究人员的极大关注,并已广泛用于解决多个领域中的不同优化问题。这种关注归因于其合理的执行时间、良好的收敛加速率以及与文献中几种备受关注的优化算法相比的高效率。本文简要概述了基本的SCA及其变体,分为改进版、多目标版和杂交版。此外,还描述了SCA在分类、图像处理、机器人路径规划、调度、径向配电网以及其他工程问题等多个领域的应用。最后,本文为SCA推荐了一些潜在的未来研究方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf58/8171367/e8aa9aa2e091/10462_2021_10026_Fig1_HTML.jpg

相似文献

1
A comprehensive survey of sine cosine algorithm: variants and applications.
Artif Intell Rev. 2021;54(7):5469-5540. doi: 10.1007/s10462-021-10026-y. Epub 2021 Jun 2.
2
A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem.
PLoS One. 2018 May 17;13(5):e0195675. doi: 10.1371/journal.pone.0195675. eCollection 2018.
4
A new Multi Sine-Cosine algorithm for unconstrained optimization problems.
PLoS One. 2021 Aug 6;16(8):e0255269. doi: 10.1371/journal.pone.0255269. eCollection 2021.
5
Economic load dispatch using memetic sine cosine algorithm.
J Ambient Intell Humaniz Comput. 2022 Feb 7:1-29. doi: 10.1007/s12652-022-03731-1.
6
Optimization of complex engineering problems using modified sine cosine algorithm.
Sci Rep. 2022 Nov 28;12(1):20528. doi: 10.1038/s41598-022-24840-z.
7
Image registration of computed tomography of lung infected with COVID-19 using an improved sine cosine algorithm.
Med Biol Eng Comput. 2022 Sep;60(9):2521-2535. doi: 10.1007/s11517-022-02606-z. Epub 2022 Jul 1.
10
An Improved Search and Rescue Algorithm for Global Optimization and Blood Cell Image Segmentation.
Diagnostics (Basel). 2023 Apr 15;13(8):1422. doi: 10.3390/diagnostics13081422.

引用本文的文献

2
MSPO: A machine learning hyperparameter optimization method for enhanced breast cancer image classification.
Digit Health. 2025 Jul 20;11:20552076251361603. doi: 10.1177/20552076251361603. eCollection 2025 Jan-Dec.
4
Chameleon swarm algorithm with Morlet wavelet mutation for superior optimization performance.
Sci Rep. 2025 Apr 22;15(1):13971. doi: 10.1038/s41598-025-97015-1.
5
6
Flower fertilization optimization algorithm with application to adaptive controllers.
Sci Rep. 2025 Feb 21;15(1):6273. doi: 10.1038/s41598-025-89840-1.
8
Uncovering the stochastic dynamics of solitons of the Chaffee-Infante equation.
Sci Rep. 2024 Aug 22;14(1):19485. doi: 10.1038/s41598-024-67116-4.
10
Multi-Strategy Improved Dung Beetle Optimization Algorithm and Its Applications.
Biomimetics (Basel). 2024 May 13;9(5):291. doi: 10.3390/biomimetics9050291.

本文引用的文献

2
Expeditious COVID-19 similarity measure tool based on consolidated SCA algorithm with mutation and opposition operators.
Appl Soft Comput. 2021 Jun;104:107197. doi: 10.1016/j.asoc.2021.107197. Epub 2021 Feb 20.
3
A Modified Sine-Cosine Algorithm Based on Neighborhood Search and Greedy Levy Mutation.
Comput Intell Neurosci. 2018 Jul 4;2018:4231647. doi: 10.1155/2018/4231647. eCollection 2018.
4
Optimization by simulated annealing.
Science. 1983 May 13;220(4598):671-80. doi: 10.1126/science.220.4598.671.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验