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Erschienen in:
How Accurate Can Instrumental Variable Models Become? Kapitel lesen Erstes Kapitel lesen

2012 | OriginalPaper | Buchkapitel

4. Model Structure Identification and the Growth of Knowledge

verfasst von : M. B. Beck, Z. Lin, J. D. Stigter

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

Verlag: 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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Vorheriges Kapitel Identifiability, and Beyond
Nächstes Kapitel Application of Minimum Distortion Filtering to Identification of Linear Systems Having Non-uniform Sampling Period
Fußnoten
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.
 
Literatur
1.
Alvarez-Vasquez, F., Sims, K.L., Cowart, L.A., Okamoto, Y., Voit, E.O., Hannun, Y.A.: Simulation and validation of modelled sphingolipid metabolism in Saccharomyces Cerevisiae. Nature 433, 425–430 (2005) CrossRef
2.
Beck, M.B.: The application of control and systems theory to problems of river pollution. Ph.D. dissertation, University of Cambridge, UK (1973)
3.
Beck, M.B.: Model structure identification from experimental data. In: Halfon, E. (ed.) Theoretical Systems Ecology: Advances and Case Studies, pp. 259–289. Academic, New York (1979)
4.
Beck, M.B.: Uncertainty, system identification and the prediction of water quality. In: Beck, M.B., van Straten, G. (eds.) Uncertainty and Forecasting of Water Quality, pp. 3–68. Springer, Berlin (1983)
5.
Beck, M.B.: Structures, failure, inference, and prediction. In: Barker, H.A., Young, P.C. (eds.) Identification and System Parameter Estimation, pp. 1443–1448. Pergamon, Oxford (1985)
6.
Beck, M.B.: Water quality modeling: a review of the analysis of uncertainty. Water Resour. Res. 23(8), 1393–1442 (1987) CrossRef
7.
Beck, M.B. (ed.): Environmental Foresight and Models: A Manifesto. Elsevier, Oxford (2002), 473 pp.
8.
Beck, M.B.: Model evaluation and performance. In: El-Shaarawi, A.H., Piegorsch, W.W. (eds.) Encyclopedia of Environmetrics, vol. 3, pp. 1275–1279. Wiley, Chichester (2002)
9.
Beck, M.B.: Structural change: a definition. In: Beck, M.B. (ed.) Environmental Foresight and Models: A Manifesto, pp. 51–60. Elsevier, Amsterdam (2002) CrossRef
10.
Beck, M.B., Young, P.C.: Systematic identification of DO-BOD model structure. J. Environ. Eng. Div. 102(5), 909–927 (1976). Proceedings American Society of Civil Engineers
11.
Beck, M.B., Stigter, J.D., Lloyd Smith, D.: D: Elasto-plastic deformation of the structure. In: Beck, M.B. (ed.) Environmental Foresight and Models: A Manifesto, pp. 323–350. Elsevier, Oxford (2002) CrossRef
12.
Beck, M.B., Gupta, H., Rastetter, E., Shoemaker, C., Tarboton, D., Butler, R., Edelson, D., Graber, H., Gross, L., Harmon, T., McLaughlin, D., Paola, C., Peters, D., Scavia, D., Schnoor, J.L., Weber, L.: Grand challenges of the future for environmental modeling. White Paper, National Science Foundation, Arlington, Virginia (2009) (ISBN: 978-1-61584-248-3)
13.
Box, G.E.P., Jenkins, G.M.: Time Series Analysis, Forecasting and Control. Holden Day, San Francisco (1970) MATH
14.
Brun, R., Reichert, P., Künsch, H.R.: Practical identifiability analysis of large environmental simulation models. Water Resour. Res. 37(4), 1015–1030 (2001) CrossRef
15.
Brun, R., Kühni, M., Siegrist, H., Gujer, W., Reichert, P.: Practical identifiability of ASM2d parameters—systematic selection and tuning of parameter subsets. Water Res. 36(16), 4113–4127 (2002) CrossRef
16.
Hunt, C.A., Ropella, G.E.P., Lam, T.N., Tang, J., Kim, S.H.J., Engelberg, J.A., Sheikh-Bahaei, S.: At the biological modeling and simulation frontier. Pharm. Res. 26(11), 2369–2400 (2009). doi:10.​1007/​s11095-009-9958-3 CrossRef
17.
Lin, Z.: Modeling environmental systems under uncertainty: towards a synthesis of data-based and theory-based models. Ph.D. dissertation, University of Georgia, Athens, Georgia (2003)
18.
19.
Lin, Z., Beck, M.B.: Understanding complex environmental systems: a dual approach. Environmetrics 18(1), 11–26 (2007b) MathSciNetCrossRef
20.
Lin, Z., Beck, M.B.: Accounting for structural error and uncertainty in a model: An approach based on model parameters as stochastic processes. Environ. Model. Softw. (2010, in press)
21.
Ljung, L.: Asymptotic behaviour of the extended Kalman filter as a parameter estimator. IEEE Trans. Autom. Control 24, 36–50 (1979) MathSciNetMATHCrossRef
22.
MacFarlane, A.G.J.: Interactive computing: a revolutionary medium for teaching and design. Comput. Control J. 1(4), 149–158 (1990) CrossRef
23.
Mooney, C.: Storm World—Hurricanes, Politics, and the Battle Over Global Warming. Harcourt, Orlando (2007)
24.
NRC: Models in Environmental Regulatory Decision Making. National Research Council, National Academy Press, Washington (2007), 267 pp
25.
NSF: Sensors for environmental observatories. Report of the NSF-sponsored Workshop, December 2004, National Science Foundation (2005), 64 pp
26.
NSF: Simulation-based engineering science: revolutionizing engineering science through simulation. Report of the National Science Foundation Blue Ribbon Panel, National Science Foundation (2006), 65 pp
27.
28.
Norton, J.P.: Optimal smoothing in the identification of linear time-varying systems. Proc. Inst. Electr. Eng. 122, 663–668 (1975) CrossRef
29.
Omlin, M., Brun, R., Reichert, P.: Biogeochemical model of lake Zürich: sensitivity, identifiability and uncertainty analysis. Ecol. Model. 141(1–3), 105–123 (2001) CrossRef
30.
Oppenheimer, M., O’Neill, B.C., Webster, M., Agrawala, S.: The limits of consensus. Science 317, 1505–1506 (2007) CrossRef
31.
Petersen, B., Gernaey, K., Vanrolleghem, PA: Practical identifiability of model parameters by combined respirometric-titrimetric measurements. Water Sci. Technol. 43(7), 347–355 (2001)
32.
Popper, K.R.: The Unending Quest: An Intellectual Autobiography. Fontana-Collins, Glasgow (1976)
33.
Raick, C., Soetart, K., Grégoire, M.: Model complexity and performance: how far can we simplify? Prog. Oceanogr. 70, 27–57 (2006) CrossRef
34.
Stigter, J.D.: The development and application of a continuous-discrete recursive prediction error algorithm in environmental systems analysis. Ph.D. dissertation, University of Georgia, Athens, Georgia (1997)
35.
Stigter, J.D., Beck, M.B.: On the development and application of a continuous-discrete recursive prediction error algorithm. Math. Biosci. 191(2), 143–158 (2004) MathSciNetMATHCrossRef
36.
Stigter, J.D., Vries, D., Keesman, K.J.: On adaptive optimal input design: a bioreactor case study. AIChE J. 52(9), 3290–3296 (2006) CrossRef
37.
Tushingham, AM, Peltier, W.R.: Validation of the ICE-3G model of Würm-Wisconsin deglaciation using a global data base of relative sea level histories. J. Geophys. Res. 97(B3), 3285–3304 (1992) CrossRef
38.
Young, P.C.: Recursive Estimation and Time Series Analysis: An Introduction. Springer, New York (1984) MATH
39.
Young, P.C.: Data-based mechanistic modelling of environmental, ecological, economic and engineering systems. Environ. Model. Softw. 12, 105–122 (1998)
40.
Young, P.C.: Nonstationary time series analysis and forecasting. Prog. Environ. Sci. 1, 3–48 (1999)
41.
Young, P.C.: The identification and estimation of nonlinear stochastic systems. In: Mees, A.I. (ed.) Nonlinear Dynamics and Statistics, pp. 127–166. Birkhäuser, Boston (2001)
42.
Young, P.C., Parkinson, S.: Simplicity out of complexity. In: Beck, M.B. (ed.) Environmental Foresight and Models: A Manifesto, pp. 251–301. Elsevier, Oxford (2002) CrossRef
43.
Young, P.C., Ratto, M.: A unified approach to environmental systems modeling. J. Stoch. Environ. Res. Risk Assess. 23, 1037–1057 (2009) CrossRef
Metadaten
Titel
Model Structure Identification and the Growth of Knowledge
verfasst von
M. B. Beck
Z. Lin
J. D. Stigter
Copyright-Jahr
2012
Verlag
Springer London
Buch
System Identification, Environmental Modelling, and Control System Design

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

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

Copyright-Jahr: 2012

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

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