2 citations · 2 across the 7 of their papers we have counts for
3 papers · 1 filter
Real-Time Surface-to-Air Missile Engagement Zone Prediction Using Simulation and Machine Learning
Joao P. A. Dantas, Diego Geraldo, Felipe L. L. Medeiros +2
Surface-to-Air Missiles (SAMs) are crucial in modern air defense systems. A critical aspect of their effectiveness is the Engagement Zone (EZ), the spatial region within which a SA…
Supervised Machine Learning for Effective Missile Launch Based on Beyond Visual Range Air Combat Simulations
Joao P. A. Dantas, Andre N. Costa, Felipe L. L. Medeiros +3
This work compares supervised machine learning methods using reliable data from constructive simulations to estimate the most effective moment for launching missiles during air com…
Weapon Engagement Zone Maximum Launch Range Estimation Using a Deep Neural Network
Joao P. A. Dantas, Andre N. Costa, Diego Geraldo +2
This work investigates the use of a Deep Neural Network (DNN) to perform an estimation of the Weapon Engagement Zone (WEZ) maximum launch range. The WEZ allows the pilot to identif…