Main Reference PaperTraffic Flow Prediction With Big Data: A Deep Learning Approach, IEEE Transactions on Intelligent Transportation Systems, 2018 [Python]
  • A deep learning based traffic flow prediction is proposed. In deep learning model, a stacked autoencoder model is used to learn generic traffic flow features, and it is trained in a layerwise greedy fashion.

Description
  • A deep learning based traffic flow prediction is proposed. In deep learning model, a stacked autoencoder model is used to learn generic traffic flow features, and it is trained in a layerwise greedy fashion.

  • To improve the traffic flow prediction performance.

  • The traffic flow features are extracted from large amount of traffic data.

Aim & Objectives
  • To improve the traffic flow prediction performance.

  • The traffic flow features are extracted from large amount of traffic data.

  • In the proposed work, the prediction layer is based on logistic regression. To further improve the performance of prediction, the more powerful predictor is contributed.

Contribution
  • In the proposed work, the prediction layer is based on logistic regression. To further improve the performance of prediction, the more powerful predictor is contributed.

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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