ArticleScientific reports2024
The analysis of ecological security and tourist satisfaction of ice-and-snow tourism under deep learning and the Internet of Things.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Exploring the antecedents of tourist satisfaction: A big data analysis of ice and snow tourism destinations.PloS one · 2026Article
- The analysis of regional ice and snow tourist destinations under back propagation neural network.Heliyon · 2024Article
- The analysis of rural tourism image optimization under the internet of things and deep learning.Scientific reports · 2024Article
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1 author.
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Abstract
This paper aims to propose a prediction method based on Deep Learning (DL) and Internet of Things (IoT) technology, focusing on the ecological security and tourist satisfaction of Ice-and-Snow Tourism (IST) to solve practical problems in this field. Accurate predictions of ecological security and tourist satisfaction in IST have been achieved by collecting and analyzing environment and tourist behavior data and combining with DL models, such as convolutional and recurrent neural networks. The experimental results show that the proposed method has significant advantages in performance indicators, such as accuracy, F1 score, Mean Squared Error (MSE), and correlation coefficient. Compared to other similar methods, the method proposed improves accuracy by 3.2%, F1 score by 0.03, MSE by 0.006, and correlation coefficient by 0.06. These results emphasize the important role of combining DL with IoT technology in predicting ecological security and tourist satisfaction in IST.
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