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  Published Paper Details:

  Paper Title

TRAFFIC COLLISION ANALYSIS AND PREDICTION

  Authors

  Abhijeet Madhukar Tote

  Keywords

Road accidents, association rules , clustering, EMM, feature extraction, top k

  Abstract


The increase in road fatalities comes as bad news. This cannot be stopped but can be controlled. The Accidents may cause due to driver�s health, Driver�s feelings, vehicle speed, climate condition, traffic conditions, road conditions, etc. Analysis and prediction on Traffic collision has gained importance in these days. The big dataset is generated every year. The proposed system works on analysis and prediction of road accidents information data using machine learning algorithms and its efficient execution. For analysis same type of accidents are clustered together using EMM algorithm and for prediction association mining is performed using Top-k Improved Association Rule Mining (IARM) algorithm. This algorithm finds the top k rules from dataset. The generated association rules are then provided to the Congestion control using Machine Framework (CCMF) and Traffic Congestion Analyzer using Mapping (TCAMP) algorithms to generate predictions. The Results are compared in terms of accuracy and efficiency with existing systems.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2008223

  Paper ID - 197964

  Page Number(s) - 2089-2095

  Pubished in - Volume 8 | Issue 8 | August 2020

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.24279

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Abhijeet Madhukar Tote,   " TRAFFIC COLLISION ANALYSIS AND PREDICTION", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.8, Issue 8, pp.2089-2095, August 2020, Available at :http://www.ijcrt.org/papers/IJCRT2008223.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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