Document Type
Presentation
Location
COAS: Math Conference Room
Start Date
6-3-2024 10:00 AM
End Date
6-3-2024 11:00 AM
Description
This project aims to improve air traffic management in emergencies. We first developed a GRU neural network to forecast weather-related airport capacity constraints using historical data, underscoring the value of real-time data analysis. We then optimized emergency evacuation air travel using Particle Swarm Optimization, demonstrating the ability to quickly aggregate evacuation flight resources cost-effectively. Finally, we provided a hybrid model combining a genetic algorithm with a neural network for evacuation planning, we show that neural network can be integrated accelerate genetic algorithms for efficient and performance assured system optimization.
Original PPT
Resource Optimization for Air Mobility Under Emergency Situations
COAS: Math Conference Room
This project aims to improve air traffic management in emergencies. We first developed a GRU neural network to forecast weather-related airport capacity constraints using historical data, underscoring the value of real-time data analysis. We then optimized emergency evacuation air travel using Particle Swarm Optimization, demonstrating the ability to quickly aggregate evacuation flight resources cost-effectively. Finally, we provided a hybrid model combining a genetic algorithm with a neural network for evacuation planning, we show that neural network can be integrated accelerate genetic algorithms for efficient and performance assured system optimization.