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GREY BOX MODELLING – BRANCHES AND EXPERIENCES

B. Sohlberg, E.W. Jacobsen
2008 IFAC Proceedings Volumes  
Further, distributed parameter modelling presents a specific challenge in that it is difficult to distinguish model reduction errors from model-data discrepancies.  ...  In this paper we divide grey box modelling into the following branches; constrained black box identification, semi-physical modelling, mechanistic modelling, hybrid modelling and distributed parameter  ...  Outcome of the Grey Box Model An Extended Kalman Filter based on the mechanistic grey box model is used to estimate both the process states and the unknown parameters describing the flow passing the squeezer  ... 
doi:10.3182/20080706-5-kr-1001.01934 fatcat:bw5ytapyynacliweyxnfxqnk6u

Network Identification Methods [article]

Young Hwan Chang, Claire Tomlin
2016 bioRxiv   pre-print
This article provides a brief overview of different approaches used to identify biological networks and reviews recent advances in network identification.  ...  Recently, network inference algorithms have grown tremendously in the field of systems biology because network identification is essential for understanding relationships between regulation mechanisms  ...  One can take a score-based approach and given a scoring function and a set of data, network inference amounts to finding the structure that maximizes the score.  ... 
doi:10.1101/071217 fatcat:whn3xzdiw5fhfacnigslcoq2fy

An Approach To Identification Of Dynamic Model For Optimization Of Fed-Batch Fermentation Processes

Donatas Levišauskas, Tomas Tekorius
2013 Information Technology and Control  
The model parameters are found by using experimental data of batch or fed-batch fermentation processes and a consecutive identification procedure, which includes preliminary estimation of the parameters  ...  The model identification relies on exploiting a versatile structure model that covers several particular structure models commonly used in bioprocess engineering practice.  ...  Identification of parameters of the nonlinear model (1)-(7) by minimizing error between experimental data and the model predictions is not a trivial task because the first approach values of model parameters  ... 
doi:10.5755/j01.itc.42.1.927 fatcat:arw7o33abfd4rgqi2zu4wbdsxe

Interpretable Semi-Mechanistic Fuzzy Models by Clustering, OLS and FIS Model Reduction [chapter]

Janos Abonyi, Hans Roubos, Robert Babuska, Ferenc Szeifert
2003 Studies in Fuzziness and Soft Computing  
A semi-mechanistic fuzzy modeling technique is proposed to obtain compact and transparent process models based on small data-sets.  ...  Semi-mechanistic models are hybrid models that consist of a white box structure based on mechanistic relationships and black-box substructures to model less defined parts.  ...  Semi-Mechanistic Model of the Process Based on the collected identification data, we first identified a standard MIMO TS model with eight rules.  ... 
doi:10.1007/978-3-540-37057-4_10 fatcat:4gvzenq6lfer3jshfxxxnrrjxm

Analyzing input and structural uncertainty of nonlinear dynamic models with stochastic, time-dependent parameters

Peter Reichert, Johanna Mieleitner
2009 Water Resources Research  
Mieleitner (2009), Analyzing input and structural uncertainty of nonlinear dynamic models with stochastic, time-dependent parameters, Water Resour. Res., 45, W10402,  ...  In contrast to the usual approach of considering bias in model output with an autoregressive error model or a stochastic process, we make the attempt to correct for bias within the model or even in model  ...  In particular, it builds on work by the research group of George Kuczera, who also kindly provided the data. This makes our results directly comparable to previous studies by this group.  ... 
doi:10.1029/2009wr007814 fatcat:27iejzj32ffafgqfarwtd7im6a

Modelling and data-based identification of heating element in continuous-time domain

Ivan Zajic, Muriel Iten, Keith J Burnham
2014 Journal of Physics, Conference Series  
A unique data-based and physically meaningful nonlinear continuous-time model of heating element is presented.  ...  The second contribution presented in this work is the parameter estimation of the derived nonlinear model in continuous-time domain itself.  ...  The presented modelling procedure has been motivated by, but not necessarily strictly follow, the 'data-based mechanistic' approach to identification and modelling of systems [2, 3, 4, 5] .  ... 
doi:10.1088/1742-6596/570/1/012003 fatcat:xm5lnrxnabfmtfmyr3iayrfbq4

Hybrid semi-parametric modeling in process systems engineering: Past, present and future

Moritz von Stosch, Rui Oliveira, Joana Peres, Sebastião Feyo de Azevedo
2014 Computers and Chemical Engineering  
The development of a hybrid semi-parametric model can offer several advantages over traditional mechanistic or data-driven modeling, as reviewed in this paper.  ...  In this paper, the most common hybrid semi-parametric modeling and parameter identification techniques are revisited.  ...  Acknowledgment Sincere thanks for financial support to the Fundac¸ão para a Ciência e a Tecnologia (References of the scholarship provided to Moritz von Stosch: SFRH/BD/36990/2007, and of the funded project  ... 
doi:10.1016/j.compchemeng.2013.08.008 fatcat:buzeagsaevhfzdc5w3zbnkj4zy

Data-based mechanistic modelling of environmental, ecological, economic and engineering systems

P YOUNG
1998 Environmental Modelling & Software  
It introduces the concept of Data-Based Mechanistic (DBM) modelling and contrasts its inductive approach with the hypotheticodeductive approaches that dominate most environmental modelling research at  ...  The paper discusses the problems associated with environmental modelling and the need to consider uncertainty in the formulation, identification, estimation and validation of environmental models.  ...  The Data-Based Mechanistic (DBM) approach to modelling discussed in this paper tries to correct these deficiencies.  ... 
doi:10.1016/s1364-8152(98)00011-5 fatcat:hm476gufqnh3ppm73zm26aot24

Identification and control of electro-mechanical systems using state-dependent parameter estimation

Alexandre Janot, Peter C. Young, Maxime Gautier
2016 International Journal of Control  
The paper describes a new alternative but related approach that exploits the State-Dependent-Parameter (SDP) method of nonlinear model estimation and compares its performance with that of IDIM-LS.  ...  The SDP method is a two-stage identification procedure able to identify the presence and graphical shape of nonlinearities in dynamic system models with a minimum of a priori assumptions.  ...  It is convenient, therefore, to introduce a state-dependent parameter that is able to cope with such nonlinearities.  ... 
doi:10.1080/00207179.2016.1209565 fatcat:rcs6m6dvrzglroqw26dvlhkufa

Appraisal of data-driven and mechanistic emulators of nonlinear simulators: The case of hydrodynamic urban drainage models

Juan Pablo Carbajal, João Paulo Leitão, Carlo Albert, Jörg Rieckermann
2017 Environmental Modelling & Software  
Many model based scientific and engineering methodologies, such as system identification, sensitivity analysis, optimization and control, require a large number of model evaluations.  ...  We compare emulators that explicitly use knowledge of the simulator's equations, i.e. mechanistic emulators based on Gaussian Processes, with purely data-driven emulators using matrix factorization.  ...  Acknowledgements The authors would like to thank Prof. Peter Reichert for his support during the development of this article. We thank Dr. David Machac for his emulation results used in Figure 6 .  ... 
doi:10.1016/j.envsoft.2017.02.006 fatcat:7oeytpzh3beb7jfef623iovh2u

Quantitative Mechanistically Based Dose-Response Modeling with Endocrine-Active Compounds

Melvin E. Andersen, Rory B. Conolly, Elaine M. Faustman, Robert J. Kavlock, Christopher J. Portier, Daniel M. Sheehan, Patrick J. Wier, Lauren Ziese
1999 Environmental Health Perspectives  
Interpretation of these data and their quantitative use in human and ecologic risk assessment will be enhanced by the availability of mechanistically based dose-response (MBDR) models to assist low-dose  ...  these approaches, and resource/data needs to accelerate model development and model acceptance by the research and the regulatory community.  ...  Coordinate with development of these new tools for hazard identification and new mechanistic tests is a need to create a set of refined dose-response assessment tools that use as much of this new data  ... 
doi:10.2307/3434556 pmid:10421774 pmcid:PMC1567506 fatcat:7ugwuxttqrdivkmnyesapnh6ua

Systems interface biology

Francis J. Doyle, Jörg Stelling
2006 Journal of the Royal Society Interface  
In the same manner, these new classes of biological problems are motivating novel developments in theoretical systems approaches.  ...  Hence, the interface between systems and biology is of mutual benefit to both disciplines.  ...  We acknowledge the financial support to F.J.D. from the Institute for Collaborative Biotechnologies through grant DAAD19-03-D-0004 from the US Army Research Office.  ... 
doi:10.1098/rsif.2006.0143 pmid:16971329 pmcid:PMC1664650 fatcat:rqtnqq6ulvc5ldya75qha7di5u

Formulation, construction and analysis of kinetic models of metabolism: A review of modelling frameworks

Pedro A. Saa, Lars K. Nielsen
2017 Biotechnology Advances  
Due to the paucity of kinetic data and the highly nonlinear structure of kinetic models, MLE-based approaches are unable to yield a representative best parameter fit given the extremely rugged (i.e., non-obtained  ...  A Formulation of the network structure integrated with fluxomic data supported by directionalities based on thermodynamic and metabolomic data, enables definition of a reference state for the ORACLE application  ... 
doi:10.1016/j.biotechadv.2017.09.005 pmid:28916392 fatcat:httsj5xitfh3xcjvbfmh7q4bye

Identification and estimation of continuous-time, data-based mechanistic (DBM) models for environmental systems

P.C. Young, H. Garnier
2006 Environmental Modelling & Software  
It then introduces a widely applicable class of new, nonlinear, State-Dependent Parameter (SDP) models.  ...  has been applied to the identification and estimation of a model for the transportation and dispersion of a pollutant in a river.  ...  So, although they cannot represent every type of nonlinear stochastic-dynamic behaviour, such SDP models (which can be extended to include multivariate state dependency with each SDP a function of more  ... 
doi:10.1016/j.envsoft.2005.05.007 fatcat:housujxcu5d7tj5fjxrafwaep4

Model-Based Monitoring of Biotechnological Processes—A Review

Velislava Lyubenova, Georgi Kostov, Rositsa Denkova-Kostova
2021 Processes  
In the literature, a large number of developments related to this topic that concern data-based and model-based sensors are presented.  ...  This gives a reason for the article to be focused on a review of model-based software sensors for biotechnological processes.  ...  A well-known approach is to consider the parameters as additional state variables without a model for their dynamics and evaluate them with an extended Kalman filter, a Luenberger observer or other type  ... 
doi:10.3390/pr9060908 fatcat:oax5mrcpmjgjdeuv3wjw7jecyu
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