A tunnel Gaussian process model for learning interpretable flight’s landing parameters

A tunnel Gaussian process model for learning interpretable flight’s landing parameters

Approach and landing accidents have resulted in a significant number of hull losses worldwide. Technologies (e.g., instrument landing system) and procedures (e.g., stabilized approach criteria) have been developed to reduce the risks. In this paper, we propose a data-driven method to learn and inter...

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Bibliographic Details
Main Authors: Goh, Sim Kuan, Lim, Zhi Jun, Alam, Sameer, Singh, Narendra Pratap
Other Authors: School of Mechanical and Aerospace Engineering
Format: Journal Article
Language:English
Published: 2021
Subjects:
Engineering::Aeronautical engineering::Aviation
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Gaussian Mixture Models
Flight Landing Parameters Learning
Online Access:https://hdl.handle.net/10356/153283

Internet

https://hdl.handle.net/10356/153283

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