南京航空航天大学学报（英文版）2023，Vol.40Issue(z2)：54-61,8.DOI:10.16356/j.1005-1120.2023.S2.008
基于机器学习模型的飞机噪声预测
Aircraft Noise Prediction Based on Machine Learning Model
摘要
Abstract
In order to explore the aircraft noise prediction methods beyond the best practice model and scientific model,this paper uses multiple linear regression model and random forest regression model to predict the aircraft noise value of Seattle-Tacoma International Airport in the summer of 2020-2022.The experiment confirm the feasibility and advantages of the machine learning model in aircraft noise prediction tasks and find that the mean R2 predicted by the random forest regression model is 74.469%,5.361%higher than that of the multiple linear regression model.The mean RMSE predicted by the random forest regression model is 0.814,0.106 lower than that of the multiple linear regression model.关键词
飞机噪声排放/飞机噪声预测/多元线性回归/随机森林回归Key words
aircraft noise emissions/aircraft noise prediction/multiple linear regression/random forest regression分类
交通工程引用本文复制引用
丰豪,周亚东,丁聪,曾维理,郭文韬..基于机器学习模型的飞机噪声预测[J].南京航空航天大学学报（英文版）,2023,40(z2):54-61,8.基金项目
This work was supported by the Na-tional Natural Science Foundation of China(No.52202442)and National Key R&D Program of China(No.2022YFB260-2403). （No.52202442）
