Review on Real-Time Rate of Climb Prediction System

Real-time estimation of the rate of climb (RoC) is a vital parameter in modern aviation, essential for ensuring optimal flight performance, safety, and energy management. This paper presents a comprehensive review of the model's architecture, the training process, evaluation metrics, and results obtained through simulation. The performance of the model, demonstrated through metrics like R² score and RMSE, indicates the effectiveness of neural networks in accurately capturing the nonlinear dynamics of flight.