Adaptive Neural Network Metamodel for Short-term Prediction of Background Ozone Level

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dc.contributor.author Wahid, HB
dc.contributor.author Ha, QP
dc.contributor.author Nguyen-Duc, H
dc.contributor.editor Ho, TB
dc.contributor.editor Zuckerman, D
dc.contributor.editor Kuonen, P
dc.contributor.editor Demaille, A
dc.contributor.editor Kutsche, RD
dc.date.accessioned 2012-02-02T11:10:08Z
dc.date.issued 2010-01
dc.identifier.citation Proceedings of 2010 IEEE-RIVF International Conference on Computing and Communication Technologies - Research, Innovation and Vision for the Future, 2010, pp. 250 - 253
dc.identifier.isbn 978-1-4244-8075-3
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/16536
dc.description.abstract Modelling is important in air quality forecasting and control. Before applying an air quality model, it is required to accurately estimate the biogenic emission. The assessment of the background ozone concentration is essential for this estimation. It has been known that the biogenic ozone level in urban areas is changing over the years, and hence information about the temporal trends in air quality data is helpful for the assessment. This paper presents a neural-network metamodel for prediction of the background ozone level in the Sydney basin. Based on measured monitoring data under non-photochemical conditions collected at a number of monitoring stations, the proposed model can reliably provide short-term predictions in the biogenic ozone trends to be used for analysis of ground-level emission impact on air quality.
dc.publisher IEEE
dc.relation.isbasedon 10.1109/RIVF.2010.5633376
dc.title Adaptive Neural Network Metamodel for Short-term Prediction of Background Ozone Level
dc.type Conference Proceeding
dc.description.version Published
dc.parent Proceedings of 2010 IEEE-RIVF International Conference on Computing and Communication Technologies - Research, Innovation and Vision for the Future
dc.journal.number en_US
dc.publocation Hanoi en_US
dc.identifier.startpage 250 en_US
dc.identifier.endpage 253 en_US
dc.cauo.name FEIT.School of Elec, Mech and Mechatronic Systems en_US
dc.conference Verified OK en_US
dc.conference IEEE-RIVF International Conference on Computing and Communication Technologies, Research Innovation, and Vision for the Future
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 000935
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom IEEE-RIVF International Conference on Computing and Communication Technologies, Research Innovation, and Vision for the Future en_US
dc.date.activity 20101101 en_US
dc.date.activity 2010-11-01
dc.location.activity Hanoi, Vietnam en_US
dc.description.keywords adaptive systems , air pollution , environmental science computing , ozone , prediction theory , radial basis function networks , metamodelling , adaptive spread, background ozone trend, Sydney basin en_US
dc.description.keywords Social Sciences
dc.description.keywords Science & Technology
dc.description.keywords Physical Sciences
dc.description.keywords Economics
dc.description.keywords Mathematics, Interdisciplinary Applications
dc.description.keywords Social Sciences, Mathematical Methods
dc.description.keywords Business & Economics
dc.description.keywords Mathematics
dc.description.keywords Mathematical Methods In Social Sciences
dc.description.keywords ECONOMICS
dc.description.keywords MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
dc.description.keywords SOCIAL SCIENCES, MATHEMATICAL METHODS
dc.description.keywords SEMIPARAMETRIC BAYESIAN-INFERENCE
dc.description.keywords QUANTILE REGRESSION
dc.description.keywords POSTERIOR DISTRIBUTIONS
dc.description.keywords STOCHASTIC VOLATILITY
dc.description.keywords MIXTURE-MODELS
dc.description.keywords WAGE STRUCTURE
dc.description.keywords DEMAND
dc.description.keywords DYNAMICS
dc.description.keywords PRIORS
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Elec, Mech and Mechatronic Systems
pubs.organisational-group /University of Technology Sydney/Strength - Built Infrastructure
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)


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