Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/3284
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSrinivasan Venkatachari.en_US
dc.date.accessioned2008-09-17T09:26:26Z-
dc.date.available2008-09-17T09:26:26Z-
dc.date.copyright2002en_US
dc.date.issued2002-
dc.identifier.urihttp://hdl.handle.net/10356/3284-
dc.description.abstractFor modeling nonlinear systems, Artificial Neural Network (ANN) offers a promising alternative compared to the more conventional methods such as the Volterra series method and the Hammerstein model. ANN models are widely used in performing time series prediction. ANN models are trained and used as a single-step ahead predictor in control application.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering-
dc.titleN-step prediction using box-Jenkins methodologyen_US
dc.typeThesisen_US
dc.contributor.supervisorDevanathan, R.en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Science (Computer Control and Automation)en_US
item.fulltextWith Fulltext-
item.grantfulltextrestricted-
Appears in Collections:EEE Theses
Files in This Item:
File Description SizeFormat 
EEE-THESES_1161.pdf
  Restricted Access
2.12 MBAdobe PDFView/Open

Page view(s) 50

604
Updated on Jul 12, 2024

Download(s)

1
Updated on Jul 12, 2024

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.