# Machine learning optimizes the military reconnaissance capabilities of drone clusters ## Path planning optimization 1. **Intensive learning application** -Use Deep Q Network (DQN) or near-end strategy optimization (PPO) algorithms to train drones to learn the optimal path -Optimize range, fuel consumption and reconnaissance coverage through reward mechanisms 2. **Group intelligence algorithm** -Application of particle swarm optimization (PSO) and ant colony algorithms to realize multi-DRONE collaborative path planning - Ensure maximum reconnaissance coverage while avoiding path overlap and redundancy 3. **Dynamic environment adaptation** -Combine LSTM or GRU networks to process time series information to predict changes in the battlefield environment -Implement online learning to adapt to sudden threats and target movements ## Target recognition enhancement 1. **Deep learning model** -Deploy lightweight CNN architecture (MobileNet, EfficientDet) to achieve edge computing -Use migration learning to overcome the scarcity of military target training data 2. **Multi-modal fusion** -Combine optical, infrared, SAR and other multi-sensor data -Adopt attention mechanism and Transformer architecture to integrate different signal characteristics 3. **Small sample learning** -Implement meta-learning and small sample learning techniques to identify rare military targets -Use data to enhance and generate confrontation network expansion training samples ## Cluster collaboration mechanism 1. **Distributed decision-making system** -Establish a distributed information sharing mechanism based on graph neural network (GNN) -Design a fault-tolerant communication protocol to prevent a single point of failure 2. **Federal learning implementation** -Share model updates while keeping communication between each machine to a minimum - Ensure that recognition capabilities can be maintained even in restricted communication environments 3. **Adaptive task assignment** -Apply multi-agent reinforcement learning to dynamically assign reconnaissance tasks -Optimize the overall reconnaissance efficiency based on the sensor capabilities and remaining energy of each UAV