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  Published Paper Details:

  Paper Title

NEURAL NETWORKS USED IN THE PREDICTION OF TRAFFIC FLOW

  Authors

  Nishanth Vaidya,  NIkhil Bharadwaj

  Keywords

Deep Learning, Neural Networks.

  Abstract


Abstract- Neural network approaches for traf?c ?ow forecasting are usually even currently based on STL models, which do not take the data from the relative tasks. But instead of using STL and MTL, using Neural Networks can improve on generalization by transferring information in training signals of extra tasks. In our Deep Learning and Neural Networks are used in the prediction of traffic flow. Using DL and NN deep architecture to predict the short-term traffic flow in an urban traffic network have been used and are effective. Comprehensive experiments will be done to show that this method is effective in forecasting traffic.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2005223

  Paper ID - 194653

  Page Number(s) - 1685-1688

  Pubished in - Volume 8 | Issue 5 | May 2020

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  Nishanth Vaidya,  NIkhil Bharadwaj,   "NEURAL NETWORKS USED IN THE PREDICTION OF TRAFFIC FLOW", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.8, Issue 5, pp.1685-1688, May 2020, Available at :http://www.ijcrt.org/papers/IJCRT2005223.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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