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Found 7 papers, 3 papers with code
Real-Time Surface-to-Air Missile Engagement Zone Prediction Using Simulation and Machine Learning
Surface-to-Air Missiles (SAMs) are crucial in modern air defense systems.
Autonomous Agent for Beyond Visual Range Air Combat: A Deep Reinforcement Learning Approach
This work contributes to developing an agent based on deep reinforcement learning capable of acting in a beyond visual range (BVR) air combat simulation environment.
Learned Tree Search for Long-Horizon Social Robot Navigation in Shared Airspace
In this work, we propose Social Robot Tree Search (SoRTS), an algorithm for the safe navigation of mobile robots in social domains.
Supervised Machine Learning for Effective Missile Launch Based on Beyond Visual Range Air Combat Simulations
This work compares supervised machine learning methods using reliable data from constructive simulations to estimate the most effective moment for launching missiles during air combat.
Enhanced Self-Organizing Map Solution for the Traveling Salesman Problem
Besides, we employed hyperparameter tuning to identify the most critical features in the algorithm.
Weapon Engagement Zone Maximum Launch Range Estimation Using a Deep Neural Network
This work investigates the use of a Deep Neural Network (DNN) to perform an estimation of the Weapon Engagement Zone (WEZ) maximum launch range.
Engagement Decision Support for Beyond Visual Range Air Combat
This work aims to provide an engagement decision support tool for Beyond Visual Range (BVR) air combat in the context of Defensive Counter Air (DCA) missions.
