Fuel estimation of commercial aircraft for the climb-out phase using gaussian process regression model

In this study, Gaussian Process Regression (GPR) is utilised to accurately estimate fuel consumption. For this purpose, ten randomly determined flights performed by Boeing B737-800 twin-engine medium-haul narrow-bodied commercial aircraft are selected. In this context, actual flight data obtained from the Flight Data Recorder (FDR) is used to estimate fuel consumption during the climb-out phase. Different statistical tests, namely Root Mean Square Error (RMSE), coefficient of determination (R2), and Mean Absolute Error (MAE), are applied to evaluate the performance of the GPR in this paper. RMSE, R2, and MAE values for GPR is calculated to be 209.41, 0.99, and 111.38, respectively. As can be seen from the results of all statistical tests, the GPR model indicates successful performance.