Literature DB >> 11385867

Practical identifiability of model parameters by combined respirometric-titrimetric measurements.

B Petersen1, K Gernaey, P A Vanrolleghem.   

Abstract

An earlier study on theoretical identifiability of parameters for a two-step nitrification model showed that a unique estimation of the yield YA1 is possible with combined respirometric-titrimetric data, contrary to the case where only one type of measurement is available. Here, the practical identifiability of model parameters was investigated via evaluation of the output sensitivity functions and the corresponding Fisher Information Matrix (FIM). It appeared that the FIM was not sufficiently powerful to predict the practical identifiability of this case with combined measurements as parameters could indeed be identified despite the fact that the FIM became singular. The accuracy of parameter estimates based on respirometric and titrimetric data and combination thereof was also investigated. Estimation on titrimetric data (Hp) was very accurate and a fast convergence of the objective function towards a minimum was obtained. The latter also holds for estimation on oxygen uptake rate data (rO), however with a lower accuracy. Parameter estimation based on oxygen concentration data (SO) was more complex but resulted in a higher accuracy. Thus, when the highest accuracy is needed it is recommended to estimate parameters initially on Hp and/or rO data, and to subsequently use these parameters as initial values for final, and more accurate estimation on SO data.

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Year:  2001        PMID: 11385867

Source DB:  PubMed          Journal:  Water Sci Technol        ISSN: 0273-1223            Impact factor:   1.915


  5 in total

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Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

2.  Use of real-time QPCR in biokinetics and modeling of two different ammonia-oxidizing bacteria growing simultaneously.

Authors:  Kyungjin Cho; Duong Xuan Nguyen; Seungyong Lee; Seokhwan Hwang
Journal:  J Ind Microbiol Biotechnol       Date:  2013-07-06       Impact factor: 3.346

3.  What do we mean by identifiability in mixed effects models?

Authors:  Marc Lavielle; Leon Aarons
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-12-10       Impact factor: 2.745

4.  Iterative approach to model identification of biological networks.

Authors:  Kapil G Gadkar; Rudiyanto Gunawan; Francis J Doyle
Journal:  BMC Bioinformatics       Date:  2005-06-20       Impact factor: 3.169

5.  Dynamic genome-scale metabolic modeling of the yeast Pichia pastoris.

Authors:  Francisco Saitua; Paulina Torres; José Ricardo Pérez-Correa; Eduardo Agosin
Journal:  BMC Syst Biol       Date:  2017-02-21
  5 in total

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