分数阶微分方程的二维尺度-3 分数欧拉小波优化算法

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computational Science Pub Date : 2024-10-28 DOI:10.1016/j.jocs.2024.102459
Fengying Zhou, Jiakun Zhang
{"title":"分数阶微分方程的二维尺度-3 分数欧拉小波优化算法","authors":"Fengying Zhou,&nbsp;Jiakun Zhang","doi":"10.1016/j.jocs.2024.102459","DOIUrl":null,"url":null,"abstract":"<div><div>A numerical scheme combining particle swarm optimization(PSO) optimization algorithm for solving fractional-order differential equations is developed by using 2D scale-3 fractional Euler wavelets, which are constructed via orthogonal Euler polynomials. The fractional integration formulas for scale-3 fractional Euler wavelets are derived under Riemann–Liouville fractional integral. The error estimation is given through the generalized fractional-order Taylor expansion and the convergence analysis of 2D scale-3 fractional Euler wavelets expansion is studied. According to the fractional integration formulas, together with the collocation method, a numerical technique is created by discretizing the fractional-order differential equation into a system of equations. Some linear and nonlinear problems are provided and PSO algorithm is applied to the numerical scheme. The numerical results are analyzed and compared with existing findings. This not only confirms the feasibility and effectuality of the proposed method but also demonstrates that PSO algorithm can enhance the numerical scheme’s performance.</div></div>","PeriodicalId":48907,"journal":{"name":"Journal of Computational Science","volume":"83 ","pages":"Article 102459"},"PeriodicalIF":3.1000,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"2D scale-3 fractional Euler wavelets optimization algorithm for fractional-order differential equations\",\"authors\":\"Fengying Zhou,&nbsp;Jiakun Zhang\",\"doi\":\"10.1016/j.jocs.2024.102459\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>A numerical scheme combining particle swarm optimization(PSO) optimization algorithm for solving fractional-order differential equations is developed by using 2D scale-3 fractional Euler wavelets, which are constructed via orthogonal Euler polynomials. The fractional integration formulas for scale-3 fractional Euler wavelets are derived under Riemann–Liouville fractional integral. The error estimation is given through the generalized fractional-order Taylor expansion and the convergence analysis of 2D scale-3 fractional Euler wavelets expansion is studied. According to the fractional integration formulas, together with the collocation method, a numerical technique is created by discretizing the fractional-order differential equation into a system of equations. Some linear and nonlinear problems are provided and PSO algorithm is applied to the numerical scheme. The numerical results are analyzed and compared with existing findings. This not only confirms the feasibility and effectuality of the proposed method but also demonstrates that PSO algorithm can enhance the numerical scheme’s performance.</div></div>\",\"PeriodicalId\":48907,\"journal\":{\"name\":\"Journal of Computational Science\",\"volume\":\"83 \",\"pages\":\"Article 102459\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational Science\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1877750324002527\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Science","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1877750324002527","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

摘要

利用通过正交欧拉多项式构造的二维标度-3分数欧拉小波,开发了一种结合粒子群优化(PSO)优化算法求解分数阶微分方程的数值方案。在黎曼-刘维尔分数积分下推导出了标度-3 分数欧拉小波的分数积分公式。通过广义分数阶泰勒展开给出了误差估计,并研究了二维标度-3 分数欧拉小波展开的收敛性分析。根据分数积分公式,结合配位法,通过将分数阶微分方程离散化为方程组,创建了一种数值技术。提供了一些线性和非线性问题,并将 PSO 算法应用于数值方案。对数值结果进行了分析,并与现有研究结果进行了比较。这不仅证实了所提方法的可行性和有效性,还证明了 PSO 算法可以提高数值方案的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
2D scale-3 fractional Euler wavelets optimization algorithm for fractional-order differential equations
A numerical scheme combining particle swarm optimization(PSO) optimization algorithm for solving fractional-order differential equations is developed by using 2D scale-3 fractional Euler wavelets, which are constructed via orthogonal Euler polynomials. The fractional integration formulas for scale-3 fractional Euler wavelets are derived under Riemann–Liouville fractional integral. The error estimation is given through the generalized fractional-order Taylor expansion and the convergence analysis of 2D scale-3 fractional Euler wavelets expansion is studied. According to the fractional integration formulas, together with the collocation method, a numerical technique is created by discretizing the fractional-order differential equation into a system of equations. Some linear and nonlinear problems are provided and PSO algorithm is applied to the numerical scheme. The numerical results are analyzed and compared with existing findings. This not only confirms the feasibility and effectuality of the proposed method but also demonstrates that PSO algorithm can enhance the numerical scheme’s performance.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Computational Science
Journal of Computational Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
5.50
自引率
3.00%
发文量
227
审稿时长
41 days
期刊介绍: Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory. The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).
期刊最新文献
Establishing a massively parallel computational model of the adaptive immune response Unsupervised continual learning by cross-level, instance-group and pseudo-group discrimination with hard attention A cluster-based opposition differential evolution algorithm boosted by a local search for ECG signal classification Community-based voting approach to enhance the spreading dynamics by identifying a group of influential spreaders in complex networks Deep dive into generative models through feature interpoint distances
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1