A double inertial embedded modified S-iteration algorithm for nonexpansive mappings: A classification approach for lung cancer detection

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dc.contributor.authorWatcharaporn Yajai
dc.contributor.authorKunrada Kankam
dc.contributor.authorJen-Chih Yao
dc.contributor.authorWatcharaporn Cholamjiak
dc.contributor.correspondenceW. Cholamjiak; Department of Mathematics, School of Science, University of Phayao, Phayao, 56000, Thailand; email: watcharaporn.ch@up.ac.th
dc.date.accessioned2025-07-07T18:16:38Z
dc.date.available2025-07-07T18:16:38Z
dc.date.issued2025
dc.description.abstractThis paper introduces a double inertial embedded modified S-iteration algorithm for finding a common fixed point of nonexpansive mappings in a real Hilbert space. A weak convergence theorem is established under suitable conditions involving control parameters. Three algorithms are directly obtained for addressing split equilibrium problems through the equivalence of nonexpansive mappings. An illustrative example in an infinite-dimensional space is provided to substantiate the proposed main algorithm. Furthermore, we highlight the practical application of these algorithms in lung cancer screening, where they are employed to optimize three different machine learning models, thereby potentially improving patient outcomes. The efficiency of the proposed algorithms is validated through comparative analysis with existing algorithms. © 2025
dc.identifier.citationCommunications in Nonlinear Science and Numerical Simulation
dc.identifier.doi10.1016/j.cnsns.2025.108978
dc.identifier.issn10075704
dc.identifier.scopus2-s2.0-105007042401
dc.identifier.urihttps://repository.dusit.ac.th/handle/123456789/7319
dc.languageEnglish
dc.publisherElsevier B.V.
dc.rights.holderScopus
dc.subjectClassification
dc.subjectDouble inertial technique
dc.subjectFixed point problem
dc.subjectLung cancer
dc.subjectMann algorithm
dc.subjectSplit equilibrium problem
dc.titleA double inertial embedded modified S-iteration algorithm for nonexpansive mappings: A classification approach for lung cancer detection
dc.typeArticle
mods.location.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-105007042401&doi=10.1016%2fj.cnsns.2025.108978&partnerID=40&md5=03c5cdd9947c8c9d2497aa6348e907e9
oaire.citation.volume150
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