Traffic accident monitoring system using deep learning

  • Authors

    • A Manikandan
    • R Anandan
    2018-04-20
    https://doi.org/10.14419/ijet.v7i2.21.12382
  • Deep learning, GPS, stochastic gradient descent.

  • A short time period in development of rural places and public vehicle transportation system globally increased. The road accident are increased by the traffic problems last five years. It is a big problem of human society. These traffic accident are how can we happen and how to solve traffic management. Here we collect the traffic accident data and GPS record data using these data to build a deep learning model of stochastic gradient descent learning algorithm method used to solve critical problem of a traffic accident risk. 

      

     

  • References

    1. [1] Eagle N, Pentland AS & Lazer D, “Inferring friendship network structure by using mobile phone dataâ€, Proceedings of the National Academy of Sciences, Vol.106, No.36, (2009), pp.15274–15278.

      [2] Fan Z, Song X & Shibasaki R, “Cityspectrum: a non-negative tensor factorization approachâ€, Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing, (2014), pp.213–223.

      [3] Grover A, Kapoor A & Horvitz E, “A deep hybrid model for weather forecastingâ€, Proceedings of the21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, (2015), pp.379–386.

      [4] Hinton GE & Salakhutdinov RR, ‘Reducing the dimensionality of data with neural networksâ€, Science, Vol.313, No.5786, (2006), pp.504–507.

      [5] Hinton G, Deng L, Yu D, Dahl GE, Mohamed AR, Jaitly N, Senior A, Vanhoucke V, Nguyen P, Sainath TN & Kingsbury B, “Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groupsâ€, Signal Processing Magazine, Vol.29, No.6, (2012), pp.82–97.

      [6] Hinton GE, Osindero S & The YW, “A fast learning algorithm for deep belief netsâ€, Neural computation, Vol.18, No.7, (2006), pp.1527–1554.

      [7] Huang W, Song G, Hong H & Xie K, “Deep architecture for traffic flow prediction: Deep belief networks with multitask learningâ€, IEEE Transactions on Intelligent Transportation Systems, (2014).

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  • How to Cite

    Manikandan, A., & Anandan, R. (2018). Traffic accident monitoring system using deep learning. International Journal of Engineering & Technology, 7(2.21), 283-287. https://doi.org/10.14419/ijet.v7i2.21.12382