Research on highway passenger segmentation based on Canopy-kmeans clustering algorithm under parallel computing framework

In order to satisfy the needs of highway passenger precise segmentation with massive historical data, a novel clustering algorithm under parallel computing framework is proposed. The average number of tickets purchased in a period is considered to build an evaluation model of highway passenger segme...

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Vydané v:	2017 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation (SmartWorld SCALCOM UIC ATC CBDCom IOP SCI) s. 1 - 6
Hlavní autori:	Ma, Jun, Luo, Shen, Wu, Liuyang, Luo, Guofu, Li, Xiaoke, Zhang, Dong
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.08.2017
Predmet:	Canopy Algorithm Clustering algorithms Computational modeling Distributed databases Highway Passenger Segmentation Indexes K-Means Algorithm Parallel Computing Parallel processing Road transportation Sparks
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