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How Accurate Can Instrumental Variable Models Become? Read chapter Read first chapter

2012 | OriginalPaper | Chapter

4. Model Structure Identification and the Growth of Knowledge

Authors : M. B. Beck, Z. Lin, J. D. Stigter

Published in: System Identification, Environmental Modelling, and Control System Design

Publisher: Springer London

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Abstract

This chapter honors Peter, then, in recounting my career-long experience (1970–2010) of staring down the devilishly difficult: the problem of model structure identification—of using models for discovery. I still regard this matter as one of the grand challenges of environmental modeling (Beck et al., White Paper, 2009). If I appear modest about our progress in the presence of such enormity, so I am. But let no-one presume that I am therefore not greatly enthused by the progress I believe I and my students (now colleagues) have made over these four decades. It has been a privilege to be allowed the time to work on such a most attractive and engaging topic.

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previous chapter Identifiability, and Beyond
next chapter Application of Minimum Distortion Filtering to Identification of Linear Systems Having Non-uniform Sampling Period
Footnotes
1
It did not, as it happens. The two co-exist fruitfully today, notwithstanding the supposed academic inferiority of the latter.
 
2
The EPCL, a platform for real-time monitoring of water quality in a variety of aquatic environments, was operated from 1997 through 2008. All the data bases gathered with it are archived in the Georgia Watershed Information System (GWIS) and are publicly and freely available for downloading and analysis at www.​georgiawis.​org.
 
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Metadata
Title
Model Structure Identification and the Growth of Knowledge
Authors
M. B. Beck
Z. Lin
J. D. Stigter
Copyright Year
2012
Publisher
Springer London
Book
System Identification, Environmental Modelling, and Control System Design

Print ISBN: 978-0-85729-973-4

Electronic ISBN: 978-0-85729-974-1

Copyright Year: 2012

DOI
https://doi.org/10.1007/978-0-85729-974-1_4