Prediction of rural tourism suitability based on multi-dimensional evaluation model

被引:0
|
作者
Li Y. [1 ]
机构
[1] School of Creative Design, Jilin University of Architecture and Technology, Changchun
关键词
evaluation model; MDTW-LSTM; modelling; neural networks; prediction method; rural folk custom; tourism suitability;
D O I
10.1680/jsmic.23.00014
中图分类号
O212 [数理统计];
学科分类号
摘要
There is an increased focus on how to improve tourism quality in rural areas. To provide reference and guidance for both tourists and tourism departments, a multi-dimensional tourism suitability model is proposed. Meteorological, travel and other data related to a tourism area were analysed, and a tourism suitability evaluation architecture model was developed. From February to September, when temperature fluctuations were more clearly defined, the prediction accuracy of the model was higher, while the test results of the root mean square error and other indicators of the model in meteorological prediction were good. The model had the highest prediction accuracy of 96.8% under multi-dimensional conditions. The model could provide accurate guidance for tourists to choose travel dates and destinations, further promoting rural tourism. © 2024 Emerald Publishing Limited: All rights reserved.
引用
收藏
页码:25 / 34
页数:9
相关论文
共 50 条
  • [1] Comprehensive prediction method for failure rate of transmission line based on multi-dimensional cloud model
    Lei, Jiazhi
    Gong, Qingwu
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2019, 13 (09) : 1672 - 1678
  • [2] Evaluation and Prediction Model for Ice-Snow Tourism Suitability under Climate Warming
    Yu, Jie
    Cai, Weiying
    Zhou, Miaolei
    ATMOSPHERE, 2022, 13 (11)
  • [3] A multi-dimensional relation model for dimensional sentiment analysis
    Xie, Housheng
    Lin, Wei
    Lin, Shuying
    Wang, Jin
    Yu, Liang-Chih
    INFORMATION SCIENCES, 2021, 579 : 832 - 844
  • [4] Neural networks for link prediction in realistic biomedical graphs: a multi-dimensional evaluation of graph embedding-based approaches
    Crichton, Gamal
    Guo, Yufan
    Pyysalo, Sampo
    Korhonen, Anna
    BMC BIOINFORMATICS, 2018, 19
  • [5] Neural networks for link prediction in realistic biomedical graphs: a multi-dimensional evaluation of graph embedding-based approaches
    Gamal Crichton
    Yufan Guo
    Sampo Pyysalo
    Anna Korhonen
    BMC Bioinformatics, 19
  • [6] FlightKoopman: Deep Koopman for Multi-Dimensional Flight Trajectory Prediction
    Lu, Jing
    Jiang, Jingjun
    Bai, Yidan
    Dai, Wenxiang
    Zhang, Wei
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS, 2025,
  • [7] Stochastic configuration networks for multi-dimensional integral evaluation
    Li, Shangjie
    Huang, Xianzhen
    Wang, Dianhui
    INFORMATION SCIENCES, 2022, 601 : 323 - 339
  • [8] A universal multi-dimensional charge and mass transfer model
    Kennell, G.
    Evitts, R. W.
    ADVANCES IN FLUID MECHANICS VIII, 2010, : 181 - 191
  • [9] Parameter probabilistic prediction for satellite power system based on unsupervised multi-dimensional sequence segmentation
    Kang, Shouqiang
    Gao, Yanjiao
    Song, Yuchen
    Zhou, Ruzhi
    Pang, Jingyue
    AEROSPACE SCIENCE AND TECHNOLOGY, 2024, 146
  • [10] Application of Improved Algorithm Based on Four-Dimensional ResNet in Rural Tourism Passenger Flow Prediction
    Chen, Xi
    Cong, Donglai
    JOURNAL OF SENSORS, 2022, 2022