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Prof. Dr. M. Jarke
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Prof. Dr. M. Jarke
RWTH Aachen
Informatik 5
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Evaluation Framework for Data Stream Mining Algorithms for Traffic State Estimation in a Data Fusion Architecture

Thesis type
  • Diplom
Student Farhad Soleimankhani
Status Finished
Submitted in 2010
Proposal on 27. Apr 2010 16:00
Proposal room Seminarraum I5
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Presentation on 21. Dec 2010 16:00
Presentation room Seminarraum I5
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The thesis is conducted in the context of the project Cooperative Cars (see the CoCar project page). We utilize information sent by the communicating cars and integrate them with traffic information derived from anonymous mobile device data and data from other sources to estimate the current traffic state on a road. The sources send out the data as data streams, i.e. as a rapid and continuous flow. The notion of data streams does not only pose new issues in data management, but also in data mining. In this work different data stream mining algorithms will be analyzed systematically according to their suitability in traffic state estimation based on the different data sources. A framework for comparing the algorithms has to be selected and to be adapted when required. Different mining algorithms are then selected and compared according to their task suitability. When required existing algorithms are adapted or a new algorithm is developed.

For more information, see the following attachment:

DA_CoCar_DM.pdf — PDF document, 147Kb

Prerequisites

Knowledge in data modeling, Java programming skills and data mining

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