Automatic Road Enforcement Detection System Using Intelligent Robust Fuzzy Trained Stochastic Neural Network
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Publisher
Springer Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-33-4389-4_15
Reference14 articles.
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2. Habtemichael, F. G., & Cetin, M. (2016). Short-term traffic flow rate forecasting based on identifying similar traffic patterns. Transportation Research Part C: Emerging Technologies, 66, 61–78. https://doi.org/10.1016/j.trc.2015.08.017.
3. Mikluščák, T., Gregor, M., Janota, A. (2012). Using neural networks for route and destination prediction in intelligent transport systems. In Mikulski, J. (Eds.), Telematics in the transport environment. TST 2012. Communications in computer and information science (Vol. 329). Berlin, Heidelberg, Springer.
4. Pamuła, T. (2012). Traffic flow analysis based on the real data using neural networks. In Mikulski, J. (Eds.), Telematics in the transport environment. TST 2012. Communications in computer and information science (Vol. 329). Berlin, Heidelberg, Springer
5. Gallo, M., & De Luca, G. (2018). Spatial extension of road traffic sensor data with artificial neural networks. Sensors, 18, 2640. https://doi.org/10.3390/s18082640.
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