RETRACTED ARTICLE: 5G network-oriented machine learning and national forest park ecotourism management

In order to improve the efficiency of national forest park ecotourism management, this paper analyzes the national forest park ecotourism management based on 5G network and machine learning and analyzes the prediction algorithm based on time series data used in the process of building the flow predi...

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Vydáno v:Neural computing & applications Ročník 34; číslo 12; s. 9353 - 9368
Hlavní autor: Yue, Yin
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Springer London 01.06.2022
Springer Nature B.V
Témata:
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Image Processing and Computer Vision
Probability and Statistics in Computer Science
S.I.: AI-based Web Information Processing
Special Issue on AI-based Web Information Processing
National forest park
Ecotourism
5G network
Machine learning
ISSN:0941-0643, 1433-3058
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Shrnutí:In order to improve the efficiency of national forest park ecotourism management, this paper analyzes the national forest park ecotourism management based on 5G network and machine learning and analyzes the prediction algorithm based on time series data used in the process of building the flow prediction network model. Moreover, this paper combines the actual data operation requirements to improve the algorithm, builds the system architecture according to the actual requirements of the national forest park ecotourism management, and performs data processing with the support of machine learning and 5G network. In addition, after constructing the system, this paper verifies the performance of the system and processes the test results through statistical methods. From the experimental analysis, it can be seen that the system constructed in this paper basically meets the needs of ecotourism management in the national forest park.
Bibliografie:ObjectType-Correction/Retraction-1
SourceType-Scholarly Journals-1
content type line 14
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-021-06313-y