Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

Enhanced tourist flow forecasting in Aosta Valley: A novel ensemble AI framework with adaptive temporal dynamics

Fig 2

Adaptive Temporal Ensemble (ATE) framework pipeline.

The system architecture displays the complete data flow from multi-source inputs through the ensemble prediction process. The pipeline begins with three parallel data streams: traffic sensor data (14 monitoring gates, 41M+ passages), meteorological records (43K+ hourly observations with 673 variables), and calendar information (52K+ records with 98 features).

Fig 2

doi: https://doi.org/10.1371/journal.pone.0336749.g002