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

• المؤلفون الرئيسيون: Goh, Sim Kuan, Lim, Zhi Jun, Alam, Sameer, Singh, Narendra Pratap
• مؤلفون آخرون: School of Mechanical and Aerospace Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2021
• الموضوعات: Engineering::Aeronautical engineering::Aviation; Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence; Gaussian Mixture Models; Flight Landing Parameters Learning
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/153283

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...