AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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.
Integrating big data analytics with sustainable development offers a new avenue for understanding complex human-environment interactions in urban spaces, particularly in urban tourism planning. However, limited research has examined how user-generated content (UGC) can translate tourists’ perceived destination images i...
Bali has experienced rapid tourism growth, reaching more than 6.3 million international visitors in 2024, which has increased the risk of overtourism and created challenges for sustainable destination management. Despite tourism being a major contributor to Bali’s economy, planning practices have not fully adopted data...
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 integration of Geographic Information Systems (GIS) and Artificial Intelligence (AI) has created transformative opportunities for tourism destination planning. This paper presents the GeoAI Tourism Intelligence Framework (GTIF), a conceptual framework integrating geospatial big data, AI algorithms, and spatial anal...
This study presents a dynamic route-planning framework implemented in Python based on an Elevated Beluga Whale Optimized Feed-Forward Backpropagation Neural Network (EBWO-FFBPNN). The dynamic route-planning framework optimizes the tourism experience by personalizing and dynamically re-adjusting route planning by utiliz...
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...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.