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

Mehdi Nosrati | Zendy; Mojtaba Hoseini | Zendy; Alireza Shirmarz | Zendy; Abbas Mirzaei | Zendy; Nayereh Hoseininia | Zendy; Morteza Barari | Zendy

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

Author(s) -

Mehdi Nosrati,

Mojtaba Hoseini,

Alireza Shirmarz,

Abbas Mirzaei,

Nayereh Hoseininia,

Morteza Barari

Publication year - 2016

Publication title -

bulletin de la société royale des sciences de liège

Language(s) - English

Resource type - Journals

ISSN - 1783-5720

DOI - 10.25518/0037-9565.6125

Subject(s) - radial basis function , computer science , multilayer perceptron , subway station , perceptron , service (business) , artificial intelligence , function (biology) , operations research , artificial neural network , transport engineering , engineering , business , marketing , evolutionary biology , biology

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.

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