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Sustainability in mobility for autonomous vehicles over smart city evaluation; using interval-valued fermatean fuzzy rough set-based decision-making model

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dc.citedby10
dc.contributor.authorIbrahim H.A.en_US
dc.contributor.authorQahtan S.en_US
dc.contributor.authorZaidan A.A.en_US
dc.contributor.authorDeveci M.en_US
dc.contributor.authorHajiaghaei-Keshteli M.en_US
dc.contributor.authorMohammed R.T.en_US
dc.contributor.authorAlamoodi A.H.en_US
dc.contributor.authorid58834376800en_US
dc.contributor.authorid57223984929en_US
dc.contributor.authorid58789685700en_US
dc.contributor.authorid55734383000en_US
dc.contributor.authorid36008663700en_US
dc.contributor.authorid57188662704en_US
dc.contributor.authorid57205435311en_US
dc.date.accessioned2025-03-03T07:44:00Z
dc.date.available2025-03-03T07:44:00Z
dc.date.issued2024
dc.description.abstractThe simulation tools geared towards promoting sustainability in Mobility as a Service (MaaS) evaluation is inherently a multi-criteria decision-making (MCDM) challenge due to three primary concerns: the criteria significance, data variability, and the expert opinions' uncertainty. Despite efforts in recent years, no current developed MaaS has fully addressed all evaluation criteria. Moreover, no research has evaluated the sustainability of MaaS in the context of determining its optimality. As such, this research's pivotal contribution is to present an evaluation of simulation tools for sustainable MaaS in autonomous vehicles operating in smart cities. This evaluation leans on the advanced extension of a newly proposed an interval-valued Fermatean fuzzy rough set (IVFFRS) incorporated within integrated MCDM methodologies. The IVFFRS is designed to capture intricate and uncertain evaluative data. The initial phase of the evaluation methodology involves formulating the evaluation criteria using an interval-valued Fermatean fuzzy rough set, fuzzily weighted for zero inconsistency. The subsequent phase adopts the interval-valued Fermatean fuzzy rough decision via the opinion score method to prioritize alternatives in light of data variations. This study evaluates ten distinct simulation tools for MaaS in autonomous vehicles based on seven criteria. The methodology's robustness is further ascertained through sensitivity and comparative analyses. ? 2023 The Authorsen_US
dc.description.natureFinalen_US
dc.identifier.ArtNo107609
dc.identifier.doi10.1016/j.engappai.2023.107609
dc.identifier.scopus2-s2.0-85178666132
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85178666132&doi=10.1016%2fj.engappai.2023.107609&partnerID=40&md5=2b213e79c132fc44955cc26d9ebc8a10
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36698
dc.identifier.volume129
dc.publisherElsevier Ltden_US
dc.relation.ispartofAll Open Access; Hybrid Gold Open Access
dc.sourceScopus
dc.sourcetitleEngineering Applications of Artificial Intelligence
dc.subjectAutonomous vehicles
dc.subjectDecision making
dc.subjectRough set theory
dc.subjectSmart city
dc.subjectAutonomous Vehicles
dc.subjectEvaluation criteria
dc.subjectFuzzy-rough sets
dc.subjectInterval-valued
dc.subjectInterval-valued fermatean fuzzy rough set
dc.subjectMobility
dc.subjectMulti criteria decision-making
dc.subjectMulticriteria decision-making
dc.subjectMulticriterion decision makings
dc.subjectRough-set based
dc.subjectSustainable development
dc.titleSustainability in mobility for autonomous vehicles over smart city evaluation; using interval-valued fermatean fuzzy rough set-based decision-making modelen_US
dc.typeArticleen_US
dspace.entity.typePublication
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