Abstract
Effective real-time traffic flow prediction can improve the status of traffic congestion. A lot of traffic flow predictive methods focus on vehicles’ specific information (such as vehicles id, position, speed, etc.). This paper proposes a novel method for predictive aggregate queries over data streams in road networks based on STES methods. The novel method obtains approximate aggregate queries results by less storage space and time consuming. Experiments show that it can better do aggregate prediction compared with the ES methods based on DynSketch, as well as SAES method based on DS.
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Feng, J., Shi, Y., Tang, Z., Rui, C., Min, X. (2014). A Novel Method for Predictive Aggregate Queries over Data Streams in Road Networks Based on STES Methods. In: Ali, M., Pan, JS., Chen, SM., Horng, MF. (eds) Modern Advances in Applied Intelligence. IEA/AIE 2014. Lecture Notes in Computer Science(), vol 8482. Springer, Cham. https://doi.org/10.1007/978-3-319-07467-2_14
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DOI: https://doi.org/10.1007/978-3-319-07467-2_14
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07466-5
Online ISBN: 978-3-319-07467-2
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