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Study into key problems in forecasting export containers in a region of China

Han, B.M., Zhu, X.N., Wong, Wing-gun, Ferreira, Luis, & Teng, J. (2002) Study into key problems in forecasting export containers in a region of China. In Wang, K. C. P., Xiao, G., Nie, L., & Yang, H. (Eds.) International conference on Traffic and Transportation Studies.

Abstract

Forecasting network data traffic is an important part of the function of planning and managing information systems. However, the contents of network data are so stochastic and complex that it is very difficult to establish stable functions to describe the mapping relationship between data flows and associated causal influences. In this paper, a multi-layer feed forward neural networks (NN) model is put forward to identify such relationship and the corresponding learning rule of NN, back-propagation (BP) algorithm, is given. In addition necessary estimation and validation processes are designed to ensure the successful implementation of the model proposed. The paper elucidates the application of NN model around the case of forecasting China west railway Transportation Management Information Systems (TMIS) network traffic. The predictive results obtained demonstrate that the NN model and the solution algorithm are very applicable for information planning on the TMIS network in west China.

Impact and interest:

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1 citations in Web of Science®

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ID Code: 2534
Item Type: Conference Paper
Additional URLs:
Keywords: Network data traffic, TMIS, neural networks, and back, propagation
ISBN: 0784406308
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500) > Transport Engineering (090507)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2002 American Society of Civil Engineers
Copyright Statement: Reproduced in accordance with the copyright policy of the publisher.
Deposited On: 14 Nov 2005
Last Modified: 11 Aug 2011 04:40

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