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Radial Basis Function Neural Network Approach to Estimate Public Transport Trips in Istanbul

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Part of the book series: Advances in Soft Computing ((AINSC,volume 29))

Abstract

The presented study comprised the employement of a neural network (NN) algorithm, radial basis function (RBF), for the purpose of daily trip flow forecasting in Istanbul Metropolitan Area. The RBF NN predictions were quite close to the observations as reflected in the selected performance criteria.

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© 2005 Springer-Verlag Berlin Heidelberg

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Celikoglu, H.B. (2005). Radial Basis Function Neural Network Approach to Estimate Public Transport Trips in Istanbul. In: Abraham, A., Dote, Y., Furuhashi, T., Köppen, M., Ohuchi, A., Ohsawa, Y. (eds) Soft Computing as Transdisciplinary Science and Technology. Advances in Soft Computing, vol 29. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32391-0_11

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  • DOI: https://doi.org/10.1007/3-540-32391-0_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25055-5

  • Online ISBN: 978-3-540-32391-4

  • eBook Packages: EngineeringEngineering (R0)

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