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dc.contributor.authorChan, Kit Yan
dc.contributor.authorYiu, Ka Fai
dc.contributor.editorHonglei Xu
dc.contributor.editorXiangyu Wang
dc.date.accessioned2017-01-30T12:06:04Z
dc.date.available2017-01-30T12:06:04Z
dc.date.created2014-05-29T20:00:17Z
dc.date.issued2014
dc.identifier.citationChan, K.Y. and Yiu, K.F. 2014. Development of neural network based traffic flow predictors using pre-processed data, in Xu, H. and Wang, X. (ed), Optimization and Control Methods in Industrial Engineering and Construction. pp. 125-138. Netherlands: Springer.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/18134
dc.identifier.doi10.1007/978-94-017-8044-5_8
dc.description.abstract

Neural networks have commonly been applied for traffic flow predictions. Generally, the past traffic flow data captured by on-road detector stations, is used to train the neural networks. However, recently research mostly focuses on development of innovative neural networks, while it lacks development of mechanisms on pre-processing traffic flow data priors on training in order to obtain more accurate neural networks. In this chapter, a simple but effective training method is proposed by incorporating the mechanisms of back-propagation algorithm and the exponential smoothing method, which is proposed to pre-process traffic flow data before training purposes. The pre-processing approach intends to aid the back-propagation algorithm to develop more accurate neural networks, as the pre-processed traffic flow data is more smooth and continuous than the original unprocessed traffic flow data. This approach was evaluated based on some sets of traffic flow data captured on a section of the freeway in Western Australia. Experimental results indicate that the neural networks developed based on this pre-processed data outperform those that are developed based on either original data or data which is preprocessed by the other pre-processing approaches.

dc.publisherSpringer
dc.subjectData cleansing
dc.subjectData pre-processing
dc.subjectTime-series forecasting
dc.subjectTraffic flow predictions
dc.subjectNeural network
dc.subjectIntelligent traffic management
dc.titleDevelopment of neural network based traffic flow predictors using pre-processed data
dc.typeBook Chapter
dcterms.source.startPage125
dcterms.source.endPage138
dcterms.source.titleOptimization and Control Methods in Industrial Engineering and Construction
dcterms.source.isbn978-94-017-8043-8
dcterms.source.placeGerman
dcterms.source.chapter8
curtin.department
curtin.accessStatusFulltext not available


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