An encoder-decoder model with self-attention mechanism for airport aviation noise estimation

Key Points

• Accurate estimation of aviation noise levels can reduce community disturbance and improve planning.
• The model leverages a self-attention mechanism to enhance feature representation, showing 15% higher accuracy than traditional models.
• Observational analysis of noise data from various airport locations was conducted, yielding significant insights into noise dynamics.
• Findings may enable better noise management strategies in urban planning, highlighting the need for advanced computational approaches.