现有研究中影响燃油消耗的特征值选择通常没有明确标准，研究成果难以与实际飞行相结合。基于塞斯纳172的飞行训练数据对通航教练机空中阶段的燃油消耗做出预测。首先，基于作者的飞行经验以及相关性分析，从飞行员操作角度选择影响燃油流量的特征值。其次，使用回归树模型拟合不同飞行状态下的燃油流量，并将飞机实际飞行状态与燃油流量预测值相对应，便于后期从飞行技术层面研究具体的节油策略。最后，使用经过超参数寻优的随机森林模型对燃油流量做出预测。实验结果表明，本文所使用的模型精度优于现有研究成果，平均绝对误差为0.286 gallon/h，均方根误差为0.496 gallon／h，残差平方和为0.968 4，平均绝对百分比误差为4.00%。

The selection of variables affecting fuel consumption in the existing studies usually has no clear criteria, and it is difficult to combine the research results with actual flight. The flight training data of a Cessna 172 was used to predict the fuel consumption during the airborne phase of general aviation trainer aircraft. Firstly, based on the authors' flight experience as well as correlation analysis, the features that influence fuel flow rate were selected from the pilot's operational perspective. Secondly, a regression tree model was used to predict fuel flow rate under different flight conditions, correlating the aircraft's actual flight status with the predicted fuel flow rate, in order to facilitate subsequent research on specific fuel-saving strategies from the flight technique perspective. Finally, a random forest model optimized with hyperparameter tuning was used to predict the fuel flow rate. The experimental results show that the accuracy of the model used is better than that of the existing research results, with a mean absolute error of 0.286 gallon/h, a root mean squared error of 0.496 gallon/h, a residual sum of squares of 0.968 4, and a mean absolute percentage error of 4.00%.