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dc.contributor.authorSemėnas, Rokas
dc.contributor.authorBaušys, Romualdas
dc.date.accessioned2023-09-18T16:17:00Z
dc.date.available2023-09-18T16:17:00Z
dc.date.issued2022
dc.identifier.other(WOS_ID)000746260500001
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/112711
dc.description.abstractIn this research, a novel adaptive frontier-assessment-based environment exploration strategy for search and rescue (SAR) robots is presented. Two neutrosophic WASPAS multi-criteria decision-making (MCDM) method extensions that provide the tools for addressing the inaccurate input data characteristics are applied to measure the utilities of the candidate frontiers. Namely, the WASPAS method built under the interval-valued neutrosophic set environment (WASPAS-IVNS) and the WASPAS method built under the m-generalised q-neutrosophic set environment (WASPAS-mGqNS). The indeterminacy component of the neutrosophic set can be considered as the axis of symmetry, and neutrosophic truth and falsity membership functions are asymmetric. As these three components of the neutrosophic set are independent, one can model the input data characteristics applied in the candidate frontier assessment process, while also taking into consideration uncertain or inaccurate input data obtained by the autonomous robot sensors. The performed experiments indicate that the proposed adaptive environment exploration strategy provides better results when compared to the baseline greedy environment exploration strategies.eng
dc.formatPDF
dc.format.extentp. 1-17
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyScopus
dc.source.urihttps://www.mdpi.com/2073-8994/14/1/179
dc.titleAdaptive autonomous robot navigation by neutrosophic WASPAS extensions
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references33
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyFundamentinių mokslų fakultetas / Faculty of Fundamental Sciences
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.studydirectionB04 - Informatikos inžinerija / Informatics engineering
dc.subject.vgtuprioritizedfieldsIK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.ensearch and rescue
dc.subject.enautonomous environment exploration
dc.subject.enneutrosophic sets
dc.subject.enmulti-criteria decision-making
dc.subject.enWASPAS-SVNS
dc.subject.enWASPAS-IVNS
dc.subject.enWASPAS-mGqNS
dcterms.sourcetitleSymmetry: Special Issue Multi-Criteria Decision-Making Techniques for Improvement Sustainability Engineering Processes II
dc.description.issueiss. 1
dc.description.volumevol. 14
dc.publisher.nameMDPI
dc.publisher.cityBasel
dc.identifier.doi000746260500001
dc.identifier.doi2-s2.0-85123096528
dc.identifier.doi85123096528
dc.identifier.doi1
dc.identifier.doi133852125
dc.identifier.doi10.3390/sym14010179
dc.identifier.elaba118339912


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