Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/109694
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dc.contributorSchool of Hotel and Tourism Management-
dc.creatorXiong, K-
dc.date.accessioned2024-11-08T06:11:22Z-
dc.date.available2024-11-08T06:11:22Z-
dc.identifier.urihttp://hdl.handle.net/10397/109694-
dc.language.isoenen_US
dc.publisherSciendoen_US
dc.rights© 2023 Keke Xiong, published by Sciendo.en_US
dc.rightsThis work is licensed under the Creative Commons Attribution alone 4.0 License (https://creativecommons.org/licenses/by/4.0).en_US
dc.rightsThe following publication Xiong, K. Optimality of analysing smart tourism destination management based on media convergence algorithms. Applied Mathematics and Nonlinear Sciences, 2024, Sciendo, vol. 9 no. 1 is available at https://doi.org/10.2478/amns.2023.2.00729.en_US
dc.subjectGaussian filteringen_US
dc.subjectLoss constraint weightsen_US
dc.subjectMedia fusionen_US
dc.subjectPixel intensity valuesen_US
dc.subjectTrajectory end directionsen_US
dc.titleOptimality of analysing smart tourism destination management based on media convergence algorithmsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume9-
dc.identifier.issue1-
dc.identifier.doi10.2478/amns.2023.2.00729-
dcterms.abstractThis paper uses a local path fusion method of medium to simulate the angular deviation between the end direction of the trajectory and the target direction according to a specific evaluation function. The media fusion algorithm is guided to achieve global optimality of the path by fusing global path planning information and avoiding local dynamic obstacles. The smart tourism and tourism management systems are fused to balance the intensity loss constraint weights and perform Gaussian filtering to derive the tourism management situation. By decomposing the highest level of tourism information and normalizing the pixel intensity values and tourism characteristic information, it was found that the smart tourism penetration rate increased by 3.6%, the total tourism revenue increased by 88.87% over the previous year, and the working variance of tourism project effectiveness was 62.430.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationApplied mathematics and nonlinear sciences, Jan. 2024, v. 9, no. 1, https://doi.org/10.2478/amns.2023.2.00729-
dcterms.isPartOfApplied mathematics and nonlinear sciences-
dcterms.issued2024-01-
dc.identifier.scopus2-s2.0-85175557922-
dc.identifier.eissn2444-8656-
dc.description.validate202411 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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