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Selection and Exploration of Cultural and Creative Tourist Attractions Based on BP Network

In order to improve the selection and exploration effect of cultural and creative tourist attractions, this paper applies BP network to the selection and search of cultural and creative tourist attractions. Moreover, this paper improves the algorithm to promote the interrelation of cultural and crea...

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Detalles Bibliográficos
Autor principal: Xing, Nian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8817836/
https://www.ncbi.nlm.nih.gov/pubmed/35132315
http://dx.doi.org/10.1155/2022/4386357
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author Xing, Nian
author_facet Xing, Nian
author_sort Xing, Nian
collection PubMed
description In order to improve the selection and exploration effect of cultural and creative tourist attractions, this paper applies BP network to the selection and search of cultural and creative tourist attractions. Moreover, this paper improves the algorithm to promote the interrelation of cultural and creative industries and tourism industries to promote each other to form a complex and changeable dynamic system and proposes a personalized recommendation model for tourist attractions based on domain adaptation. Domain adaptation can effectively reduce the distribution difference between different data. In addition, this paper combines experimental research to verify the system model of this paper. The research results show that the cultural and creative tourist attractions selection search system based on the BP network proposed in this paper has a good selection effect of tourist attractions and has an important role in promoting the development of cultural and creative tourism.
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spelling pubmed-88178362022-02-06 Selection and Exploration of Cultural and Creative Tourist Attractions Based on BP Network Xing, Nian Comput Intell Neurosci Research Article In order to improve the selection and exploration effect of cultural and creative tourist attractions, this paper applies BP network to the selection and search of cultural and creative tourist attractions. Moreover, this paper improves the algorithm to promote the interrelation of cultural and creative industries and tourism industries to promote each other to form a complex and changeable dynamic system and proposes a personalized recommendation model for tourist attractions based on domain adaptation. Domain adaptation can effectively reduce the distribution difference between different data. In addition, this paper combines experimental research to verify the system model of this paper. The research results show that the cultural and creative tourist attractions selection search system based on the BP network proposed in this paper has a good selection effect of tourist attractions and has an important role in promoting the development of cultural and creative tourism. Hindawi 2022-01-29 /pmc/articles/PMC8817836/ /pubmed/35132315 http://dx.doi.org/10.1155/2022/4386357 Text en Copyright © 2022 Nian Xing. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Xing, Nian
Selection and Exploration of Cultural and Creative Tourist Attractions Based on BP Network
title Selection and Exploration of Cultural and Creative Tourist Attractions Based on BP Network
title_full Selection and Exploration of Cultural and Creative Tourist Attractions Based on BP Network
title_fullStr Selection and Exploration of Cultural and Creative Tourist Attractions Based on BP Network
title_full_unstemmed Selection and Exploration of Cultural and Creative Tourist Attractions Based on BP Network
title_short Selection and Exploration of Cultural and Creative Tourist Attractions Based on BP Network
title_sort selection and exploration of cultural and creative tourist attractions based on bp network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8817836/
https://www.ncbi.nlm.nih.gov/pubmed/35132315
http://dx.doi.org/10.1155/2022/4386357
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