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An ATC instruction processing-based trajectory prediction algorithm designing
by
Yin, Suwan
, Wang, Xuan
, Mao, Yi
, Wu, Xiaoyong
, Jiang, Weiyu
, Xu, Qucheng
in
Air traffic control
/ Aircraft
/ Aircraft control
/ Algorithms
/ Artificial Intelligence
/ Artificial neural networks
/ Chinese languages
/ Cognitive linguistics
/ Communication
/ Computational Biology/Bioinformatics
/ Computational Science and Engineering
/ Computer Science
/ Construction grammar
/ Data Mining and Knowledge Discovery
/ Grammar theories
/ Image Processing and Computer Vision
/ Language usage
/ Linguistics
/ Natural language
/ Natural language processing
/ Neural networks
/ Ontology
/ Prepositions
/ Probability and Statistics in Computer Science
/ S.I: Human-in-the-loop Machine Learning
/ Semantic analysis
/ Semantics
/ Special Issue on Human-in-the-loop Machine Learning and its Applications
/ Syntactic analysis
/ Syntactic structures
/ Syntax
/ Teaching
/ Theoretical linguistics
/ Trajectory analysis
/ Unstructured data
/ Voice communication
2023
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An ATC instruction processing-based trajectory prediction algorithm designing
by
Yin, Suwan
, Wang, Xuan
, Mao, Yi
, Wu, Xiaoyong
, Jiang, Weiyu
, Xu, Qucheng
in
Air traffic control
/ Aircraft
/ Aircraft control
/ Algorithms
/ Artificial Intelligence
/ Artificial neural networks
/ Chinese languages
/ Cognitive linguistics
/ Communication
/ Computational Biology/Bioinformatics
/ Computational Science and Engineering
/ Computer Science
/ Construction grammar
/ Data Mining and Knowledge Discovery
/ Grammar theories
/ Image Processing and Computer Vision
/ Language usage
/ Linguistics
/ Natural language
/ Natural language processing
/ Neural networks
/ Ontology
/ Prepositions
/ Probability and Statistics in Computer Science
/ S.I: Human-in-the-loop Machine Learning
/ Semantic analysis
/ Semantics
/ Special Issue on Human-in-the-loop Machine Learning and its Applications
/ Syntactic analysis
/ Syntactic structures
/ Syntax
/ Teaching
/ Theoretical linguistics
/ Trajectory analysis
/ Unstructured data
/ Voice communication
2023
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An ATC instruction processing-based trajectory prediction algorithm designing
by
Yin, Suwan
, Wang, Xuan
, Mao, Yi
, Wu, Xiaoyong
, Jiang, Weiyu
, Xu, Qucheng
in
Air traffic control
/ Aircraft
/ Aircraft control
/ Algorithms
/ Artificial Intelligence
/ Artificial neural networks
/ Chinese languages
/ Cognitive linguistics
/ Communication
/ Computational Biology/Bioinformatics
/ Computational Science and Engineering
/ Computer Science
/ Construction grammar
/ Data Mining and Knowledge Discovery
/ Grammar theories
/ Image Processing and Computer Vision
/ Language usage
/ Linguistics
/ Natural language
/ Natural language processing
/ Neural networks
/ Ontology
/ Prepositions
/ Probability and Statistics in Computer Science
/ S.I: Human-in-the-loop Machine Learning
/ Semantic analysis
/ Semantics
/ Special Issue on Human-in-the-loop Machine Learning and its Applications
/ Syntactic analysis
/ Syntactic structures
/ Syntax
/ Teaching
/ Theoretical linguistics
/ Trajectory analysis
/ Unstructured data
/ Voice communication
2023
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An ATC instruction processing-based trajectory prediction algorithm designing
Journal Article
An ATC instruction processing-based trajectory prediction algorithm designing
2023
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Overview
The radiotelephony communication is a voice communication mode between air traffic service unit and aircraft currently. The control instruction is a kind of unstructured data, so that the automatic systems cannot use understand its semantic. If control instruction is regarded as a sort of special “natural language,” methods such as syntax analysis and sematic analysis can be adopted to generate the structured instruction. The correct recognition of the language must be important for the control instruction. However, the control instruction in Chinese is different from the general use of Chinese language in form, resulting in prepositions becoming important for semantic analysis. This paper proposes a deep neural network-based Chinese language control construction algorithm for the trajectory prediction. In particular, analysis of sematic characteristics of control instruction is realized by using cognitive linguistics theory and construction grammar theory. The control instruction is then designed by the semantic ontology. Based on the deep neural networks by considering the word sequence of instruction as the inputs. The test results have demonstrated the effectiveness of the proposed algorithm with a developed entity extracting model. (The results are quantified using the BiLSTM-LAN-CRF in detail.)
Publisher
Springer London,Springer Nature B.V
Subject
/ Aircraft
/ Computational Biology/Bioinformatics
/ Computational Science and Engineering
/ Data Mining and Knowledge Discovery
/ Image Processing and Computer Vision
/ Ontology
/ Probability and Statistics in Computer Science
/ S.I: Human-in-the-loop Machine Learning
/ Special Issue on Human-in-the-loop Machine Learning and its Applications
/ Syntax
/ Teaching
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