TL;DR
A hybrid deep learning architecture combining Convolutional Neural Networks, Bidirectional Long Short-Term Memory, and an Attention Mechanism is developed to capture complex spatial and temporal dependencies in tourist flow patterns and provides an effective tool for visitor flow forecasting, spatial management, and sustainable tourism planning.
This study demonstrates how integrating big data analytics, computer vision, and spatial analysis can support smart-city solutions, sustainable destination management, and destination marketing and provides policymakers with a replicable methodological blueprint for evidence-based spatial planning and consumer-centered...
Comparisons of Random Forest and XGBoost algorithms in predicting the popularity of tourist destinations in Bali indicate that nature-based and cultural tourism destinations remain dominant, particularly in Badung, Jembrana, and Gianyar Regencies.
As tourism shifts from sightseeing to experience-oriented consumption, understanding how tourist perception differs across heterogeneous destination types and spatial scales remains challenging. Using 23,439 Volunteered Geographic Information (VGI) reviews archived for six destinations in Shangrao, China, this study co...
The GeoAI Tourism Intelligence Framework (GTIF), a conceptual framework integrating geospatial big data, AI algorithms, and spatial analytics to support evidence-based destination planning and management, is presented.
The dynamic route-planning framework optimizes the tourism experience by personalizing and dynamically re-adjusting route planning by utilizing a comprehensive data set to achieve superior prediction accuracy, route efficiency, and personalization compared to conventional methods.
Reliable traffic flow forecasting is a core component of intelligent transportation systems; however, many current approaches are still unable to simultaneously model spatial interdependencies and long-term temporal correlations, particularly in cross-sea corridors that exhibit directional heterogeneity and pronounced...
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