Estimation of public transport trips by feed forward back propagation artificial neural networks; A case study for Istanbul

Çelikoğlu H. B., Akad M.

8th Online World Conference on Soft Computing, ELECTR NETWORK, 29 September - 10 October 2003, pp.27-36 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1007/3-540-32400-3_3
  • Country: ELECTR NETWORK
  • Page Numbers: pp.27-36
  • Istanbul Technical University Affiliated: Yes

Abstract

Artificial neural networks are one of the recently explored advanced technologies, which show promise in the area of transportation engineering. However, in contrast to the availability of a large number of successful application demonstrations, it is hard to find studies in the literature that provide systematic examinations of the state-of-the-art, the application domains, and the applicability of artificial neural networks to transportation problems. On the other hand, some unseen artificial neural network development has been motivated by transportation engineering objectives. Therefore, this study presents the development of a neural network paradigm for the purpose of daily trip flow forecasting.