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Recurrent Neural Networks and Decision Trees based model implementation on the GTFS big data of the city of Pune to predict traffic congestion in a multi class-based approach.

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GTFS

  • Paper accepted at ICDDS

  • The GTFS, or General Transit Feed Specification, is an international standard for planning public transportation and its spatial and temporal components in metropolitan areas .

  • To create our models and make inferences, we use the city of Pune, India as a case study. The Pune Mahanagar Parivahan Mahamandal Limited makes the Pune GTFS statistics available.

  • The data is broken down into several csv files, including agency.csv, calender.csv, feed info.csv, routes.csv, shapes.csv, stop_times.csv, stops.csv, translation.csv and trips.csv.
  • Each of these files provides a collection of fields that can be used to determine the spatial and temporal characteristics of a given bus.

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Recurrent Neural Networks and Decision Trees based model implementation on the GTFS big data of the city of Pune to predict traffic congestion in a multi class-based approach.

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