%0 Journal Article
%T 民航机场TAF预报指导产品的开发与设计<br>Development and Design of TAF Forecast Guidance Products for Airports
%A 朱国栋
%J Modeling and Simulation
%P 1173-1178
%@ 2324-870X
%D 2022
%I Hans Publishing
%R 10.12677/MOS.2022.114107
%X 本文利用2015年至2021年数值预报和机场观测历史数据，采用深度学习方法建立机场要素预报模型，并通过TAF报文规则库，实现要素预报转换为TAF预报的分时段预报产品，为民航机场预报人员提供一种新的预报参考产品。<br />
This paper uses the numerical forecast and historical data of airport observation from 2015 to 2021, adopts the deep learning method to establish the airport element forecast model, and through the TAF message rule base, realizes the time-based forecast product converted from the element forecast to the TAF forecast, which provides a new forecast reference product for civil aviation airport forecasters.&nbsp;
%K 机场预报，客观指导预报，机器学习<br>Airport Forecast
%K Objective Guidance Forecast
%K Machine Learning
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=53983