Neural Network Based Models for Short-Term Traffic Flow Forecasting Using a Hybrid Exponential Smoothing and Levenberg–Marquardt Algorithm

Neural Network Based Models for Short-Term Traffic Flow Forecasting Using a Hybrid Exponential Smoothing and Levenberg–Marquardt Algorithm

This paper proposes a novel neural network (NN) training method that employs the hybrid exponential smoothing method and the Levenberg–Marquardt (LM) algorithm, which aims to improve the generalization capabilities of previously used methods for training NNs for short-term traffic flow forecasting....

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Bibliographic Details
Main Authors: Chan, Kit Yan, Dillon, Tharam, Singh, Jaipal, Chang, Elizabeth
Format: Journal Article
Published: IEEE Intelligent Transportation Systems Society 2011
Subjects:
neural networks (NNs)
Exponential smoothing method
short-term - traffic flow forecasting
Levenberg-Marquardt (LM) algorithm
Online Access:http://hdl.handle.net/20.500.11937/28800

Internet

http://hdl.handle.net/20.500.11937/28800

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