Main Reference PaperOptimizing Taxi Driver Profit Efficiency- A Spatial Network-based Markov Decision Process Approach, IEEE Transactions on Big Data, 2018[Java/Hadoop]
  • This work investigates the recommendation of the best taxi to improve the driver’s business efficiency. In order to improve the overall profit of taxi drivers, this system proposes a novel Spatial Network-based Markov Decision Process and recommend a better driving directions. Given a set of historical taxi records and the current status of a vacant taxi, this work is to find the best move for this taxi to maximize the profit in the near future.

Description
  • This work investigates the recommendation of the best taxi to improve the driver’s business efficiency. In order to improve the overall profit of taxi drivers, this system proposes a novel Spatial Network-based Markov Decision Process and recommend a better driving directions. Given a set of historical taxi records and the current status of a vacant taxi, this work is to find the best move for this taxi to maximize the profit in the near future.

  • To maximize the profit of taxi driver’s.

  • To recommend better driving directions within the short time interval.

Aim & Objectives
  • To maximize the profit of taxi driver’s.

  • To recommend better driving directions within the short time interval.

  • Efficient recommendation algorithm is contributed.

Contribution
  • Efficient recommendation algorithm 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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