Results 21 to 30 of about 649,096 (355)

Vulnerability and Resilience Analysis of the Air Traffic Control Sector Network in China

Sustainability, 2020
Sustainability and its component resilience have become an important issue that cannot be neglected in airspace planning and development. Resilience, as an emerging system concept, is critical to sustainability in many fields.
Xinglong Wang, S. Miao, Junqing Tang
semanticscholar   +1 more source

A Normal Wiggly Pythagorean Hesitant Fuzzy Bidirectional Projection Method and Its Application in EV Power Battery Recycling Mode Selection

IEEE Access, 2020
As a useful mathematical tool to solve the multi-attribute decision-making (MADM) problems, Pythagorean hesitant fuzzy set (PHFS) permits decision makers (DMs) to give several evaluation values in membership and non-membership degrees.
Chengxiu Yang, Qianzhe Wang, Weidong Peng, Jiaqiang Zhang, Jie Zhu   +4 more
doaj   +1 more source

Air Traffic Control Capacity Planning Under Demand and Capacity Provision Uncertainty

Transportation Science, 2020
In air traffic management, a fundamental decision with large cost implications is the planning of future capacity provision.
S. Starita, A. Strauss, Xin Fei, Radosav Jovanovic, N. Ivanov, Goran Pavlović, Frank Fichert   +6 more
semanticscholar   +1 more source

Toward Individual-Sensitive Automation for Air Traffic Control Using Convolutional Neural Networks

Journal of Air Transportation, 2020
Lack of trust and lack of acceptance caused by strategic mismatches in problem-solving have been identified as obstacles in the introduction of workload-alleviating automation in air traffic contro...
S. V. Rooijen, J. Ellerbroek, C. Borst, E. Kampen   +3 more
semanticscholar   +1 more source

Panoramic Convolutional Long Short-Term Memory Networks for Combat Intension Recognition of Aerial Targets

IEEE Access, 2020
Aiming at the limitation that traditional methods for combat intention recognition of aerial targets are difficult to effectively capture the essential characteristics of intelligence information, we design a novel deep learning method, Panoramic ...
Junjie Xue, Jie Zhu, Jiyang Xiao, Sheng Tong, Ling Huang   +4 more
doaj   +1 more source

Research on automatic pilot repetition generation method based on deep reinforcement learning

Frontiers in Neurorobotics, 2023
Using computers to replace pilot seats in air traffic control (ATC) simulators is an effective way to improve controller training efficiency and reduce training costs.
Weijun Pan, Peiyuan Jiang, Yukun Li, Zhuang Wang, Junxiang Huang   +4 more
doaj   +1 more source

The Airbus Air Traffic Control speech recognition 2018 challenge: towards ATC automatic transcription and call sign detection [PDF]

Interspeech, 2018
In this paper, we describe the outcomes of the challenge organized and run by Airbus and partners in 2018 on Air Traffic Control (ATC) speech recognition.
Thomas Pellegrini, Jérôme Farinas, Estelle Delpech, François Lancelot   +3 more
semanticscholar   +1 more source

Air Channel Planning Based on Improved Deep Q-Learning and Artificial Potential Fields

Aerospace, 2023
With the rapid advancement of unmanned aerial vehicle (UAV) technology, the widespread utilization of UAVs poses significant challenges to urban low-altitude safety and airspace management.
Jie Li, Di Shen, Fuping Yu, Renmeng Zhang   +3 more
doaj   +1 more source

Air Traffic Controller Workload Level Prediction using Conformalized Dynamical Graph Learning [PDF]

Advanced Engineering Informatics, 2023
Air traffic control (ATC) is a safety-critical service system that demands constant attention from ground air traffic controllers (ATCos) to maintain daily aviation operations. The workload of the ATCos can have negative effects on operational safety and
Yutian Pang, Jueming Hu, Christopher S. Lieber, N. Cooke, Yongming Liu   +4 more
semanticscholar   +1 more source

Exploring the Use of Invalid Action Masking in Reinforcement Learning: A Comparative Study of On-Policy and Off-Policy Algorithms in Real-Time Strategy Games

Applied Sciences, 2023
Invalid action masking is a practical technique in deep reinforcement learning to prevent agents from taking invalid actions. Existing approaches rely on action masking during policy training and utilization.
Yueqi Hou, Xiaolong Liang, Jiaqiang Zhang, Qisong Yang, Aiwu Yang, Ning Wang   +5 more
doaj   +1 more source