@inproceedings{5f7be61487324fa3bff801508eb060d5,
title = "Pilot behavior modeling using LSTM network: A case study",
abstract = "Traditional behavior modeling methods rely on the knowledge representation derived from the induction and abstraction of subject matter experts, leading to the high barrier and long modeling period. To tackle this problem, we focus on a new behavior modeling approach, which extracts behavior knowledge from behavior data using recurrent neural network (RNN). A case study, take-off behavior modeling using long short-term memory (LSTM) network, was carried out in three phases: the data recording phase, the offline model training phase and the online model execution phase. A three-layer neural network was constructed to learn the pattern of take-off manipulations. The resulting take-off behavior model performed well to {\textquoteleft}pilot{\textquoteright} an airplane in the real-time test.",
keywords = "Behavior modeling, Flight simulation, LSTM, RNN",
author = "Yanan Zhou and Zihao Fu and Guanghong Gong",
note = "Publisher Copyright: {\textcopyright} Springer Science+Business Media Singapore 2016.; 16th Asia Simulation Conference and SCS Autumn Simulation Multi-Conference, AsiaSim/SCS AutumnSim 2016 ; Conference date: 08-10-2016 Through 11-10-2016",
year = "2016",
doi = "10.1007/978-981-10-2666-9\_46",
language = "英语",
isbn = "9789811026652",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "458--465",
editor = "Lin Zhang and Xiao Song and Yunjie Wu",
booktitle = "Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems - 16th Asia Simulation Conference and SCS Autumn Simulation Multi-Conference, AsiaSim/SCS AutumnSim 2016, Proceedings",
address = "德国",
}