Please use this identifier to cite or link to this item: https://elib.vku.udn.vn/handle/123456789/4110
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dc.contributor.authorVu, Van Vien-
dc.contributor.authorPhan, Van Thanh-
dc.date.accessioned2024-08-20T07:25:27Z-
dc.date.available2024-08-20T07:25:27Z-
dc.date.issued2023-12-
dc.identifier.issn2224-2899-
dc.identifier.uri10.37394/23207.2023.20.235-
dc.identifier.urihttps://elib.vku.udn.vn/handle/123456789/4110-
dc.descriptionWseas Transactions on Business and Economics; PP: 2773-2780.vi_VN
dc.description.abstractCurrently, many researchers pay more attention to improving the accuracy of the Grey forecasting model. One of tendency is focused on the modification of the accumulated generating operation. In 2015, some scholars used the r-fractional order accumulation to improve the accuracy. However, With the desire of users to have a set of forecasting tools as accurate as possible. This paper based on the flexibility parameter of r-accumulated generation operation proposed the systematic approach by optimizing the number of r for improving the precision. To verify the performance in advance of the proposed approach, three case examples were used, the simulation results demonstrated that the proposed systematic approach provides very remarkable predictive performance with the accuracy performance of the proposed approach being higher than other models in comparison. Furthermore, the real case in forecasting the number of tourism visits to Quang Ninh was also conducted to compare the performance of models. The empirical results show that the proposed model will get a higher accuracy performance with the lowest MAPE =19.722%. This result offers valuable insights for Quang Ninh policymakers in building and developing policies regarding tourism industry management in the future.vi_VN
dc.language.isoenvi_VN
dc.publisherWseas Transactions on Business and Economicsvi_VN
dc.subjectGMr (1,1)vi_VN
dc.subjectfractional order accumulationvi_VN
dc.subjectoptimizationvi_VN
dc.subjectsystematic approachvi_VN
dc.subjectaccuracyvi_VN
dc.subjectnumber of touristsvi_VN
dc.subjectQuang Ninh provincevi_VN
dc.titleOptimization of GMr (1,1) Model and Its Application in Forecast the Number of Tourist Visits to Quang Ninh Provincevi_VN
dc.typeWorking Papervi_VN
Appears in Collections:NĂM 2023

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