A Deep Sequence-to-Sequence Method for Aircraft Landing Speed Prediction Based on QAR Data

[1]  Trevor Hastie,et al.  The Elements of Statistical Learning , 2001 .

[2]  Hui Sun,et al.  A Landing Operation Performance Evaluation System Based on Flight Data , 2017, HCI.

[3]  Changxu Wu,et al.  Effects of flare operation on landing safety: A study based on ANOVA of real flight data , 2018 .

[4]  Changxu Wu,et al.  An analysis of flight Quick Access Recorder (QAR) data and its applications in preventing landing incidents , 2014, Reliab. Eng. Syst. Saf..

[5]  Carlos J. Pérez,et al.  A Bayesian-Network-based Approach to Risk Analysis in Runway Excursions , 2019 .

[6]  Lloyd N. Trefethen,et al.  Barycentric Lagrange Interpolation , 2004, SIAM Rev..

[7]  Yoshua Bengio,et al.  Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.

[8]  Yue Xie,et al.  The study on hard landing prediction model with optimized parameter SVM method , 2016, 2016 35th Chinese Control Conference (CCC).

[9]  Xavier Olive,et al.  Recent Advances in Anomaly Detection Methods Applied to Aviation , 2019 .

[10]  Vijay Manikandan Janakiraman,et al.  Explaining Aviation Safety Incidents Using Deep Temporal Multiple Instance Learning , 2017, KDD.

[11]  David Ríos Insua,et al.  Bayesian Network for Managing Runway Overruns in Aviation Safety , 2019 .

[12]  Jianjun Yu,et al.  A Novel Method of Overrun Risk Measurement and Assessment Using Large Scale QAR Data , 2018, 2018 IEEE Fourth International Conference on Big Data Computing Service and Applications (BigDataService).

[13]  Chung Choo Chung,et al.  Sequence-to-Sequence Prediction of Vehicle Trajectory via LSTM Encoder-Decoder Architecture , 2018, 2018 IEEE Intelligent Vehicles Symposium (IV).

[14]  Xu Li,et al.  CurveCluster: Automated Recognition of Hard Landing Patterns Based on QAR Curve Clustering , 2019, 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI).

[15]  Chao Tong,et al.  A novel deep learning method for aircraft landing speed prediction based on cloud-based sensor data , 2018, Future Gener. Comput. Syst..

[16]  Ratan Khatwa,et al.  Flight Safety Foundation Approach-and-Landing Accident Reduction Task Force - Analysis of Critical Factors During Approach and Landing in Accidents and Normal Flight: Data Acquisition and Analysis Working Group Final Report , 1999 .

[17]  Jun Li,et al.  An innovative deep architecture for aircraft hard landing prediction based on time-series sensor data , 2018, Appl. Soft Comput..

[18]  Joaquin Quiñonero Candela,et al.  Practical Lessons from Predicting Clicks on Ads at Facebook , 2014, ADKDD'14.

[19]  Rosa María Arnaldo Valdés,et al.  Prediction of aircraft safety incidents using Bayesian inference and hierarchical structures , 2018 .

[20]  Michelle Kirby,et al.  An Application of DBSCAN Clustering for Flight Anomaly Detection During the Approach Phase , 2020 .

[21]  Christopher D. Manning,et al.  Effective Approaches to Attention-based Neural Machine Translation , 2015, EMNLP.

[22]  Finn V. Jensen,et al.  Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.