暂无分享,去创建一个
[1] Michelle Kirby,et al. An Application of DBSCAN Clustering for Flight Anomaly Detection During the Approach Phase , 2020 .
[2] Inseok Hwang,et al. Data-Driven Precursor Detection Algorithm for Terminal Airspace Operations , 2019 .
[3] Enrique Onieva,et al. Multi-head CNN-RNN for multi-time series anomaly detection: An industrial case study , 2019, Neurocomputing.
[4] Aditi Chattopadhyay,et al. Real-time anomaly detection framework using a support vector regression for the safety monitoring of commercial aircraft , 2020, Adv. Eng. Informatics.
[5] Nikunj C. Oza,et al. Using ADOPT Algorithm and Operational Data to Discover Precursors to Aviation Adverse Events , 2018 .
[6] Ashok N. Srivastava,et al. Multiple kernel learning for heterogeneous anomaly detection: algorithm and aviation safety case study , 2010, KDD.
[7] Dimitri N. Mavris,et al. Towards online prediction of safety-critical landing metrics in aviation using supervised machine learning , 2020 .
[8] Inseok Hwang,et al. Challenges and Opportunities in Flight Data Mining: A Review of the State of the Art , 2016 .
[9] Dimitri N. Mavris,et al. A Supervised Learning Approach for Safety Event Precursor Identification in Commercial Aviation , 2020, AIAA AVIATION 2020 FORUM.
[10] Eric Granger,et al. Multiple instance learning: A survey of problem characteristics and applications , 2016, Pattern Recognit..
[11] Timothy J Logan. Error prevention as developed in airlines. , 2008, International journal of radiation oncology, biology, physics.
[12] Dimitri N. Mavris,et al. Anomaly Detection in General-Aviation Operations Using Energy Metrics and Flight-Data Records , 2018 .
[13] Xi-Lin Li,et al. A Multiclass Multiple Instance Learning Method with Exact Likelihood , 2018, 1811.12346.
[14] Naren Ramakrishnan,et al. Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning , 2016, KDD.
[15] Vijay Manikandan Janakiraman,et al. Explaining Aviation Safety Incidents Using Deep Temporal Multiple Instance Learning , 2017, KDD.
[16] Inseok Hwang,et al. Incremental-Learning-Based Unsupervised Anomaly Detection Algorithm for Terminal Airspace Operations , 2019, Journal of Aerospace Information Systems.
[17] Xavier Olive,et al. Recent Advances in Anomaly Detection Methods Applied to Aviation , 2019 .
[18] Dimitri N. Mavris,et al. Trajectory Clustering within the Terminal Airspace Utilizing a Weighted Distance Function , 2020, Proceedings.
[19] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[20] Dimitri N. Mavris,et al. Deep Spatio-Temporal Neural Networks for Risk Prediction and Decision Support in Aviation Operations , 2021, J. Comput. Inf. Sci. Eng..
[21] Michelle Kirby,et al. Critical Parameter Identification for Safety Events in Commercial Aviation Using Machine Learning , 2020, Aerospace.
[22] Natalia Gimelshein,et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.
[23] Tejas G. Puranik,et al. Identification of Instantaneous Anomalies in General Aviation Operations Using Energy Metrics , 2020 .
[24] Francisco Herrera,et al. An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes , 2011, Pattern Recognit..
[25] Brett Lantz. Machine learning with R : discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R , 2015 .
[26] Nadeem Iftikhar,et al. Outlier Detection in Sensor Data using Ensemble Learning , 2020, KES.
[27] A deep sequence‐to‐sequence method for accurate long landing prediction based on flight data , 2021 .
[28] 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..
[29] Stuart Matthews. The Potential for Improving Aviation Safety and Reducing the Accident Rate , 2003 .
[30] Tejas G. Puranik,et al. Machine Learning Approach to the Analysis of Traffic Management Initiatives , 2020 .
[31] Milad Memarzadeh,et al. Unsupervised Anomaly Detection in Flight Data Using Convolutional Variational Auto-Encoder , 2020, Aerospace.
[32] Roy E. Welsch,et al. Anomaly detection via a Gaussian Mixture Model for flight operation and safety monitoring , 2016 .
[33] Kanishka Bhaduri,et al. Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms , 2013, J. Aerosp. Inf. Syst..
[34] Padmanabhan Menon,et al. A Modeling Environment for Assessing Aviation Safety , 2019 .
[35] Jaideep Srivastava,et al. Detection of Precursors to Aviation Safety Incidents Due to Human Factors , 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.