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Mehdi Nosrati, Mojtaba Hoseini, Alireza Shirmarz, Abbas Mirzaei Somarin, Nayereh Hoseininia & Morteza Barari

Application of MLP and RBF Methods in Prediction of Travelling within thecity

(Volume 85 - Année 2016 — Actes de colloques — Special edition)
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Abstract

Forecasting ofTravelling within the city demand is necessary for the correct operations of subway stations. This includes the provision of station security, management and better service to passengers will be. In this paper we are compared multilayer perceptron(MLP) and Radial Basis Function (RBF) models together for prediction of travelling within the city. The models are trained and assessed on dataset of Aliabad subway station in Tehran.

Keywords : artificial neural network, multilayer perceptron, radial basis function., urban travels

Pour citer cet article

Mehdi Nosrati, Mojtaba Hoseini, Alireza Shirmarz, Abbas Mirzaei Somarin, Nayereh Hoseininia & Morteza Barari, «Application of MLP and RBF Methods in Prediction of Travelling within thecity», Bulletin de la Société Royale des Sciences de Liège [En ligne], Volume 85 - Année 2016, Actes de colloques, Special edition, 1392 - 1396 URL : https://popups.uliege.be/0037-9565/index.php?id=6125.

A propos de : Mehdi Nosrati

Department of Computer Engineering, Payame Noor University(PNU), P.O.Box,19395-3697 Tehran, Iran

A propos de : Mojtaba Hoseini

Faculty of Information, Communications and Security Technology, Malek Ashtar University of Technology, Tehran, Iran

A propos de : Alireza Shirmarz

Faculty of Information, Communications and Security Technology, Malek Ashtar University of Technology, Tehran, Iran

A propos de : Abbas Mirzaei Somarin

Department of Computer Engineering, Islamic Azad University, Ardebil Branch, Ardebil, Iran

A propos de : Nayereh Hoseininia

Department of Computer Engineering, Payame Noor University(PNU), P.O.Box,19395-3697 Tehran, Iran

A propos de : Morteza Barari

Faculty of Information, Communications and Security Technology, Malek Ashtar University of Technology, Tehran, Iran