Ship Spatiotemporal Key Feature Point Online Extraction Based on AIS Multi-Sensor Data Using an Improved Sliding Window Algorithm

Large volumes of automatic identification system (AIS) data provide new ideas and methods for ship data mining and navigation behavior pattern analysis. However, large volumes of big data have low unit values, resulting in the need for large-scale computing, storage, and display. Learning efficiency...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 19; H. 12; S. 2706
Hauptverfasser:	Gao, Miao, Shi, Guo-You
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 16.06.2019 MDPI
Schlagworte:	AIS Algorithms Artificial intelligence Automobiles Big Data big data mining Cameras Clustering Data analysis Data compression Data mining Efficiency feature online extraction International conferences key feature point Machine learning Methods Pattern recognition Sensors ship behavior sliding window algorithm spatiotemporal Time series Vehicles Wavelet transforms United States > US China ship behavior big data mining key feature point spatiotemporal feature online extraction AIS sliding window algorithm
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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