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Prediction interval-based neural network modelling of polystyrene polymerization reactor - a new perspective of data-based modelling

Hosen,MA, Khosravi,A, Nahavandi,S and Creighton,D 2014, Prediction interval-based neural network modelling of polystyrene polymerization reactor - a new perspective of data-based modelling, in WCECS 2012 : Proceedings of the 2012 World Congress on Engineering & Compuer Science, Elsevier, Amsterdam, The Netherlands, pp. 2041-2051, doi: 10.1016/j.cherd.2014.02.016.

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Title Prediction interval-based neural network modelling of polystyrene polymerization reactor - a new perspective of data-based modelling
Author(s) Hosen,MAORCID iD for Hosen,MA orcid.org/0000-0001-8282-3198
Khosravi,AORCID iD for Khosravi,A orcid.org/0000-0001-6927-0744
Nahavandi,SORCID iD for Nahavandi,S orcid.org/0000-0002-0360-5270
Creighton,DORCID iD for Creighton,D orcid.org/0000-0002-9217-1231
Conference name Engineering & Computer Science. World Congress (2012 : San Francisco, California)
Conference location San Francisco, California
Conference dates 24-26 Oct. 2012
Title of proceedings WCECS 2012 : Proceedings of the 2012 World Congress on Engineering & Compuer Science
Publication date 2014
Start page 2041
End page 2051
Total pages 11
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Keyword(s) Neural network
Polymerization reactor
Prediction interval
Uncertainty
Science & Technology
Technology
Engineering, Chemical
Engineering
FUZZY CONTROL METHOD
BATCH POLYMERIZATION
GENETIC ALGORITHM
TEMPERATURE CONTROL
OPTIMIZATION
QUALITY
Notes Also published in Chemical Engineering Research and Design v.92, 2014 p.2041-2051.
ISSN 0263-8762
1744-3563
Language eng
DOI 10.1016/j.cherd.2014.02.016
Field of Research 080110 Simulation and Modelling
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2014, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30069408

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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Citation counts: TR Web of Science Citation Count  Cited 10 times in TR Web of Science
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