Applying Data Mining in Prediction and Classification of Urban Traffic

Data mining is a branch of computer science which recently has a great use for enterprises. Applying data mining methods, huge databases have been analyzed and processed. Data mining techniques are usually hired to mine knowledge and models from enormous data sets for prediction of new events. Furth...

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Bibliographic Details
Published in2009 WRI World Congress on Computer Science and Information Engineering Vol. 3; pp. 674 - 678
Main Authors Nejad, S.K., Seifi, F., Ahmadi, H., Seifi, N.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2009
Subjects
Classification
Computer science
Data analysis
Data engineering
Data mining
Decision Tree
Knowledge engineering
Prediction
Sampling methods
Telecommunication traffic
Testing
Traffic control
Urban Traffic
Wireless sensor networks
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Summary:Data mining is a branch of computer science which recently has a great use for enterprises. Applying data mining methods, huge databases have been analyzed and processed. Data mining techniques are usually hired to mine knowledge and models from enormous data sets for prediction of new events. Furthermore these techniques are commonly used in fields which generate great amount of data that can not be processed by ordinary methods. During the last decade traffic management became a new field of science which produced unlimited data, and this amount of data needed new methods to be processed. It is clear that one of the most important fields in traffic management is Traffic prediction. As a result data mining methods were chosen to generate dependable patterns. In this paper we applied Classification methods to learn traffic behavior and prediction of new events.
ISBN:9780769535074
0769535070
DOI:10.1109/CSIE.2009.906