Radial basis function neural network approach to estimate public transport trips in Istanbul

Hilmi Berk Celikoglu

doi:10.1007/3-540-32391-0_11

Radial basis function neural network approach to estimate public transport trips in Istanbul

Hilmi Berk Celikoglu^*

^*Corresponding author for this work

Department of Civil Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Soft Computing as Transdisciplinary Science and Technology - Proceedings of the 4th IEEE International Workshop, WSTST 2005
Publisher	Springer Verlag
Pages	31-40
Number of pages	10
Edition	AISC
ISBN (Print)	3540250557, 9783540250555
DOIs	https://doi.org/10.1007/3-540-32391-0_11
Publication status	Published - 2005
Event	4th IEEE International Workshop on Soft Computing as Transdisciplinary Science and Technology, WSTST 2005 - Muroran, Japan Duration: 25 May 2005 → 27 May 2005

Publication series

Name	Advances in Soft Computing
Number	AISC
ISSN (Print)	1615-3871
ISSN (Electronic)	1860-0794

Conference

Conference	4th IEEE International Workshop on Soft Computing as Transdisciplinary Science and Technology, WSTST 2005
Country/Territory	Japan
City	Muroran
Period	25/05/05 → 27/05/05

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

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10.1007/3-540-32391-0_11

Cite this

@inproceedings{3feb245eaace4fe9bd71459442d9578f,

title = "Radial basis function neural network approach to estimate public transport trips in Istanbul",

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.",

author = "Celikoglu, \{Hilmi Berk\}",

year = "2005",

doi = "10.1007/3-540-32391-0\_11",

language = "English",

isbn = "3540250557",

series = "Advances in Soft Computing",

publisher = "Springer Verlag",

number = "AISC",

pages = "31--40",

booktitle = "Soft Computing as Transdisciplinary Science and Technology - Proceedings of the 4th IEEE International Workshop, WSTST 2005",

address = "Germany",

edition = "AISC",

note = "4th IEEE International Workshop on Soft Computing as Transdisciplinary Science and Technology, WSTST 2005 ; Conference date: 25-05-2005 Through 27-05-2005",

}

Celikoglu, HB 2005, Radial basis function neural network approach to estimate public transport trips in Istanbul. in Soft Computing as Transdisciplinary Science and Technology - Proceedings of the 4th IEEE International Workshop, WSTST 2005. AISC edn, Advances in Soft Computing, no. AISC, Springer Verlag, pp. 31-40, 4th IEEE International Workshop on Soft Computing as Transdisciplinary Science and Technology, WSTST 2005, Muroran, Japan, 25/05/05. https://doi.org/10.1007/3-540-32391-0_11

Radial basis function neural network approach to estimate public transport trips in Istanbul. / Celikoglu, Hilmi Berk.
Soft Computing as Transdisciplinary Science and Technology - Proceedings of the 4th IEEE International Workshop, WSTST 2005. AISC. ed. Springer Verlag, 2005. p. 31-40 (Advances in Soft Computing; No. AISC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Radial basis function neural network approach to estimate public transport trips in Istanbul

AU - Celikoglu, Hilmi Berk

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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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U2 - 10.1007/3-540-32391-0_11

DO - 10.1007/3-540-32391-0_11

M3 - Conference contribution

AN - SCOPUS:84878782940

SN - 3540250557

SN - 9783540250555

T3 - Advances in Soft Computing

SP - 31

EP - 40

BT - Soft Computing as Transdisciplinary Science and Technology - Proceedings of the 4th IEEE International Workshop, WSTST 2005

PB - Springer Verlag

T2 - 4th IEEE International Workshop on Soft Computing as Transdisciplinary Science and Technology, WSTST 2005

Y2 - 25 May 2005 through 27 May 2005

ER -

Radial basis function neural network approach to estimate public transport trips in Istanbul

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