Application of MLP and RBF Methods in Prediction of Travelling within thecity
Mehdi Nosrati,
Department of Computer Engineering, Payame Noor University(PNU), P.O.Box,19395-3697 Tehran, Iran
Mojtaba Hoseini,
Faculty of Information, Communications and Security Technology, Malek Ashtar University of Technology, Tehran, Iran
Alireza Shirmarz,
Faculty of Information, Communications and Security Technology, Malek Ashtar University of Technology, Tehran, Iran
Abbas Mirzaei Somarin,
Department of Computer Engineering, Islamic Azad University, Ardebil Branch, Ardebil, Iran
Nayereh Hoseininia,
Department of Computer Engineering, Payame Noor University(PNU), P.O.Box,19395-3697 Tehran, Iran
Morteza Barari,
Faculty of Information, Communications and Security Technology, Malek Ashtar University of Technology, Tehran, Iran
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.