Neural Network Apply to predict aircraft trajectory for conflict resolution

被引:0
|
作者
Kaidi, R. [1 ]
Lazaar, M. [2 ]
Ettaouil, M. [1 ]
机构
[1] Fac Sci & Technol, Modeling & Sci Comp Lab, Fes, Morocco
[2] Abdelmalek Essaadi Univ, Natl Sch Appl Sci, Tetouan, Morocco
关键词
Artificial Neural Netork (ANNs); Optimization Multilayer Perceptron Architecture (OMPA); Air Traffic Management(ATM); Collision Avoidance; MULTILAYER PERCEPTRONS;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Today, Air Traffic keep increasing, for this raison, many research programs focus on collision avoidance technique. Aircraft trajectory prediction is a critical issue for Air Traffic Management (ATM). A safe and efficient prediction is a prerequisite for the implementation of automated tools that detect and solve conflicts between trajectories. Moreover, regarding the safety constraints, it could be more reasonable to predict intervals rather than precise aircraft positions. This paper a twofold objective; the first one, we develop an approach based on Artificial Neural Networks (ANNs), called Optimization of Multilayer Perceptron Architecture (OMPA), the second one, we use this approach to forecast trajectory in vertical plane to solve conflicts between two aircrafts in airspace.
引用
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页数:6
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