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Public Transportation BigData Clustering

Tomislav Galba ; J.J. Strossmayer University of Osijek, Faculty of Electrical Engineering
Zoran Balkić ; J.J. Strossmayer University of Osijek, Faculty of Electrical Engineering
Goran Martinović ; J.J. Strossmayer University of Osijek, Faculty of Electrical Engineering

Puni tekst: engleski, pdf (1004 KB) str. 21-26 preuzimanja: 888* citiraj
APA 6th Edition
Galba, T., Balkić, Z. i Martinović, G. (2013). Public Transportation BigData Clustering. International journal of electrical and computer engineering systems, 4. (1.), 21-26. Preuzeto s https://hrcak.srce.hr/133181
MLA 8th Edition
Galba, Tomislav, et al. "Public Transportation BigData Clustering." International journal of electrical and computer engineering systems, vol. 4., br. 1., 2013, str. 21-26. https://hrcak.srce.hr/133181. Citirano 24.11.2020.
Chicago 17th Edition
Galba, Tomislav, Zoran Balkić i Goran Martinović. "Public Transportation BigData Clustering." International journal of electrical and computer engineering systems 4., br. 1. (2013): 21-26. https://hrcak.srce.hr/133181
Harvard
Galba, T., Balkić, Z., i Martinović, G. (2013). 'Public Transportation BigData Clustering', International journal of electrical and computer engineering systems, 4.(1.), str. 21-26. Preuzeto s: https://hrcak.srce.hr/133181 (Datum pristupa: 24.11.2020.)
Vancouver
Galba T, Balkić Z, Martinović G. Public Transportation BigData Clustering. International journal of electrical and computer engineering systems [Internet]. 2013 [pristupljeno 24.11.2020.];4.(1.):21-26. Dostupno na: https://hrcak.srce.hr/133181
IEEE
T. Galba, Z. Balkić i G. Martinović, "Public Transportation BigData Clustering", International journal of electrical and computer engineering systems, vol.4., br. 1., str. 21-26, 2013. [Online]. Dostupno na: https://hrcak.srce.hr/133181. [Citirano: 24.11.2020.]

Sažetak
An increase in the use of GPS modules and cell phones with location services has created a need for new ways of collecting and storing data. Considering a fairly large number of devices, data collected in such way in most cases take up a vast amount of space on servers while on the other hand, they represent a source of very useful information. A large number of companies use this method of data collection in order to create prediction models, reports and data analysis. As an object of observation, we use the database of a modern public transportation system which contains information about vehicle telemetry. In this paper, we will describe the application and result analysis of some well-known clustering algorithms in order to solve public transportation problems like traffic congestion, passenger transport, etc.

Ključne riječi
analysis; big data; clustering; GPS; public transportation

Hrčak ID: 133181

URI
https://hrcak.srce.hr/133181

Posjeta: 1.128 *