Research on Methodologies and Applications of Flight Delay Prediction Models Based on Deep Learning
The global development trends in civil aviation informatization show that,this industry has been experiencing a transformation driven by integration of big data and AI technologies.This article discusses how to conduct machine learning and deep neural network modeling to predict macro trend of nationwide flight delays,and then take the predicted results as a reference for adjusting the flight delay insurance premium coefficients for the following year.This research elaborates the entire process from data processing,data analysis,prediction modeling to the application of prediction results,and summarizes a methodology applicable to other fields in the industry.Meanwhile,the article takes the"ground handling node-time prediction at domestic airports"as an example to discuss the application of this methodology in scenarios such as optimizing airport operational resources.It aims to inspire the empowerment of intelligent operations by integrating big data and deep learning,leverage data resource advantages of Chinese civil aviation industry,and contribute to the progress of data assetization.
NETL
NSTL
万方数据
