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January 1, 2026International Journal of Computational Intelligence Studies

Automatic prediction of tourist travel trajectory using joint graph convolutional neural network

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Key Points

The goal is to automatically predict the travel trajectory of tourists using advanced neural network techniques.
Utilized a joint graph convolutional neural network to analyze travel data.
Designed experiments with varying parameters to test prediction accuracy.
Evaluated performance against traditional methods.
Achieved a significant increase in prediction accuracy compared to conventional algorithms.
Demonstrated the model's effectiveness in real-world tourist scenarios.
Highlighted potential applications in travel planning and tourism management.

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Implication

Demonstrates automatic prediction of travel trajectories in tourists, suggesting improved travel planning efficiency.

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Cite This Study

Renzhong Jin (2026) studied this question.

synapsesocial.com/papers/6a338d50630953a74978e571 https://doi.org/10.1504/ijcistudies.2026.10079163

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