An ensemble-learning method for potential traffic hotspots detection on heterogeneous spatio-temporal data in highway domain

Inter-city highway plays an important role in modern urban life and generates sensory data with spatio-temporal characteristics. Its current situation and future trends are valuable for vehicles guidance and transportation security management. As a domain routine analysis, daily detection of traffic...

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Bibliographic Details
Published in:	Journal of cloud computing : advances, systems and applications Vol. 9; no. 1; pp. 1 - 11
Main Authors:	Ding, Weilong, Xia, Yanqing, Wang, Zhe, Chen, Zhenyu, Gao, Xingyu
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 11-05-2020 Springer Nature B.V SpringerOpen
Subjects:	Big Data Computer Communication Networks Computer Science Computer System Implementation Computer Systems Organization and Communication Networks Domains Edge computing security and privacy Ensemble learning Error reduction Highway Information Systems Applications (incl.Internet) Meteorology Regression analysis Security management Software Engineering/Programming and Operating Systems Spatio-temporal data Spatiotemporal data Special Purpose and Application-Based Systems Traffic models Traffic trends Traffic volume Trends Big Data Spatio-temporal data Ensemble learning Highway Traffic trends
Online Access:	Get full text
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