Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/109694
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Title: Optimality of analysing smart tourism destination management based on media convergence algorithms
Authors: Xiong, K 
Issue Date: Jan-2024
Source: Applied mathematics and nonlinear sciences, Jan. 2024, v. 9, no. 1, https://doi.org/10.2478/amns.2023.2.00729
Abstract: This 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.
Keywords: Gaussian filtering
Loss constraint weights
Media fusion
Pixel intensity values
Trajectory end directions
Publisher: Sciendo
Journal: Applied mathematics and nonlinear sciences 
EISSN: 2444-8656
DOI: 10.2478/amns.2023.2.00729
Rights: © 2023 Keke Xiong, published by Sciendo.
This work is licensed under the Creative Commons Attribution alone 4.0 License (https://creativecommons.org/licenses/by/4.0).
The 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.
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