Research on GRNN Model for Short-term Air Traffic Flow Management

被引：0
|
作者：
Zhan, Wang [1 ]
Shu, Wu [2 ]
机构：
[1] Nanjing Univ Aeronaut & Astronaut, Coll Civil Aviat, Nanjing 210016, Peoples R China
[2] Nanjing Univ, Sch Management & Engn, Nanjing 210093, Jiangsu, Peoples R China
来源：
INFORMATION TECHNOLOGY APPLICATIONS IN INDUSTRY, PTS 1-4 | 2013年 / 263-266卷
关键词：
ST-TFMP(short-term traffic flow management); dynamic network flow; artificial Intelligence system; GRNN(general regression neural network);
D O I：
10.4028/www.scientific.net/AMM.263-266.3244
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
For the exigent requirement of short-term air traffic flow optimized dispatching, this paper analyzes dynamic behavior and network flow algorithm of short-term air traffic flow management, presents evacuation based ST-TFMP dynamic network flow algorithm, builds ST-TFMP GRNN model. The model is verified by simulation experiment, the results show it is feasible. The model improves precision of short-term air traffic flow management, saves time and cost, and it also actualizes the intelligence short-term air traffic flow management.
引用
收藏
页码：3244 / +
页数：2
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