A Multi-strategy Improved Dung Beetle Optimisation Algorithm and its Application

A Multi-strategy Improved Dung Beetle Optimisation Algorithm and its Application | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Multi-strategy Improved Dung Beetle Optimisation Algorithm and its Application First WeiGuang Gu, Second Fang Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4170581/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 16 You are reading this latest preprint version Abstract In order to solve the shortcomings of Dung Beetle Optimizer such as low convergence accuracy and easy to fall into local optimum, a multi-strategy improved Dung Beetle Optimizer (IDBO) is proposed. Firstly, the Cubic chaotic mapping strategy is introduced to improve the diversity of the initial population. Secondly, the global exploration strategy in the Fishhawk algorithm is introduced to give the dung beetle algorithm the exploration ability of identifying the optimal region and escaping from the local optimum, which initially improves the convergence speed and optimality-seeking accuracy of the algorithm. Finally, the dung beetle foraging behaviour is perturbed using the adaptive t-distribution perturbation strategy, making the dung beetle algorithm improve the global exploitation ability and local exploration ability while further accelerate its speed of convergence. The effectiveness of the three improved strategies is verified by testing and analysing the CEC2021 and CEC2017 test functions. The optimization results of the improved algorithms and the comparison algorithms are subjected to convergence analysis and Wilcoxon rank sum test, which proves that the IDBO algorithm has good convergence speed and optimization accuracy. In addition, the IDBO algorithm is adopted to optimise parameters of the HKELM prediction model which is applied to the short-term PV power prediction simulation and comparison experiments. Experimental results show that the IDBO-HKELM prediction model can effectively improve the prediction accuracy of short-term PV power, which further verifies the feasibility and validity of the IDBO algorithm in solving the problems of practical applications. Dung Beetle Optimizer Cubic Chaos Mapping Strategy Osprey Optimization Algorithm Short-term PV power forecast Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 28 Aug, 2024 Reviewers agreed at journal 28 Aug, 2024 Reviews received at journal 28 Aug, 2024 Reviews received at journal 28 Aug, 2024 Reviewers agreed at journal 28 Aug, 2024 Reviewers agreed at journal 28 Aug, 2024 Reviewers agreed at journal 28 Aug, 2024 Reviewers agreed at journal 28 Aug, 2024 Reviewers agreed at journal 28 Aug, 2024 Reviewers agreed at journal 28 Aug, 2024 Reviewers agreed at journal 28 Aug, 2024 Reviewers agreed at journal 28 Mar, 2024 Reviewers invited by journal 28 Mar, 2024 Editor assigned by journal 28 Mar, 2024 Submission checks completed at journal 28 Mar, 2024 First submitted to journal 26 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4170581","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":285604543,"identity":"144f1958-f065-4439-8c9f-58ad1c3d1f6b","order_by":0,"name":"First WeiGuang Gu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYBACNvb+hw8k/9nw8DMcPkCcFj6eM8wGFmxpcpKNxxKI0yInkcMmUcF22Nig+YwBkQ5jyD0mcYOHOXED25mPN94w2MnpNhDUci7ZcoYEW+J2nrObLecwJBubHSCkhbHB8LaEAU/izhlnt0nzMBxI3EZQCzODgfSfBInEDfffPCNSCxuPkYTEAQNjgwNn2IjUwsOWbCDZkCAn2XDM2HKOARF+kZ//+OADyYb/oKh8eONNhZ0cQS0oQIKHyKhB1kKqjlEwCkbBKBgRAABDF0KU35x/1gAAAABJRU5ErkJggg==","orcid":"","institution":"Shanghai Dianji University","correspondingAuthor":true,"prefix":"","firstName":"First","middleName":"WeiGuang","lastName":"Gu","suffix":""},{"id":285604544,"identity":"5343e950-ee7f-4969-9498-b9f2d0ea15ec","order_by":1,"name":"Second Fang Wang","email":"","orcid":"","institution":"Shanghai Dianji University","correspondingAuthor":false,"prefix":"","firstName":"Second","middleName":"Fang","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-03-26 14:29:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4170581/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4170581/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53882532,"identity":"4ba25422-bcc2-45bc-9bb4-d915b11a58e3","added_by":"auto","created_at":"2024-04-01 18:06:12","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4280466,"visible":true,"origin":"","legend":"","description":"","filename":"LATEX2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4170581/v1_covered_0f1e236c-d468-41f6-9eb4-3103de2f3b87.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Multi-strategy Improved Dung Beetle Optimisation Algorithm and its Application","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cluster-computing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Cluster Computing](https://www.springer.com/journal/10586)","snPcode":"10586","submissionUrl":"https://submission.nature.com/new-submission/10586/3","title":"Cluster Computing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Dung Beetle Optimizer, Cubic Chaos Mapping Strategy, Osprey Optimization Algorithm, Short-term PV power forecast","lastPublishedDoi":"10.21203/rs.3.rs-4170581/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4170581/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"In order to solve the shortcomings of Dung Beetle Optimizer such as low convergence accuracy and easy to fall into local optimum, a multi-strategy improved Dung Beetle Optimizer (IDBO) is proposed. 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