Development of an Intelligent System of Determinating the Coordinates and the Speed of the Train

1. Karpushenko, N.I., Velichko, D.V., Kolmogorova, T.V. (2011) The problem of ensuring safety at railway crossing. Transport of Russian Federation, 4 (35), 47-50.Search in Google Scholar

2. Evans, E. (2011) Fatal accidents at railway level crossings in Great Britain 1946-2009. Accident Analysis and Prevention, 43(5), 1837-1845.10.1016/j.aap.2011.04.01921658512Search in Google Scholar

3. Silla, A., Kallberg, V-P. (2012) The development of railway safety in Finland. Accident Analysis and Prevention, 45, 737-744.10.1016/j.aap.2011.09.04322269565Search in Google Scholar

4. Rakotonairy, A., Soole, D., Larue, G. (2010) Use of ITS improve level crossings safety. Proc. 11th Level Crossingymp. 2010. Tokyo, 38-51.Search in Google Scholar

5. Russell, S., Norvig, P. (2003) Artificial Intelligence: A Modern Approach (Second Edition). New Jersey: Prentice Hall.Search in Google Scholar

6. Luther, D.F. (2003) Artificial Intelligence: Strategies and methods for solving complex problems. Moscow: Williams.Search in Google Scholar

7. Arkatov, V.S., Arkatov, Ju. V. and other. (2006) The track circuit main railways. Directory. Moscow: OOO Missija-M.Search in Google Scholar

8. Atabekov, G.I. (2009) Theoretical Foundations of Electrical. Linear circuits. Moscow: Lahn.Search in Google Scholar

9. Volkov, E.A., Sankovskiy, E.I., Sidorovich, D.U. (2005) Theory of linear electric circuits of railway automation, remote control and communication. Marshrut.Search in Google Scholar

10. Tu, J., Gonzalez, R. (1978) Principles of pattern recognition. Moscow: World.Search in Google Scholar

11. Tarasov, E.M. (1978) The principles of recognition in the qualifiers of rail lines. Moscow: World. P. 118.Search in Google Scholar

12. Potapov, A.S. (2007) Pattern recognition and machine perception: The general approach based on the principle of minimal length opisaniya. Saint Petersburg: University of Technology.Search in Google Scholar

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