AeroPowerNet: Fixed-Wing UAV Power Consumption Estimation with an AI-Driven Hybrid Deep Learning Framework

Keyphrases

• Vehicle Power 100%
• Power Consumption Estimation 100%
• Unmanned Aerial Vehicle 100%
• AI-driven 100%
• Fixed-wing Unmanned Aerial Vehicles 100%
• Hybrid Deep Learning Framework 100%
• Power Consumption 66%
• Hybrid Model 66%
• Power Consumption Model 66%
• Normalized Root-mean-square Error (NRMSE) 66%
• Deep Learning 33%
• Electric Power 33%
• Air Speed 33%
• Flight Data 33%
• Aviation Industry 33%
• Flight Control 33%
• Data-driven Approach 33%
• Physics-based 33%
• Long Short-term Memory Neural Network 33%
• Flight Phase 33%
• Aerial Vehicle 33%
• Mission Planning 33%
• Flight Parameters 33%
• Power Utilization 33%
• Instantaneous Power 33%
• Flight Operations 33%
• LSTM-GRU 33%
• Flight Activity 33%
• Planning Optimization 33%
• GRU-Transformer 33%

Physics

• Pilotless Aircraft 100%
• Deep Learning Method 100%
• Artificial Intelligence 100%
• Airspeed 20%
• Physics 20%
• Flight Control 20%
• Long Short-Term Memory Network 20%