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Identification of parametric models : from experimental data
Eric Walter,Luc Pronzato +1 more
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The article was published on 1997-01-01 and is currently open access. It has received 1251 citations till now. The article focuses on the topics: Parametric model & Experimental data.read more
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Nonlinear prediction by kriging, with application to noise cancellation
TL;DR: A semi-parametric approach based on kriging is suggested for nonlinear prediction that makes the approach much more flexible than those based on parametric behavioural models, and accurate predictions are obtained for extremely short-training sequences.
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Earth climate identification vs. anthropic global warming attribution
TL;DR: This paper presents the first major attempt for climate system identification in the sense of the systems theory – in the hope to significantly reduce the uncertainty ranges.
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Dynamic multi-compartmental modelling of metal bioaccumulation in fish: Identifiability implications
TL;DR: A compartmental model structure is developed aiming to obtain the maximum amount of information from published experimental data and be further used to predict metal bioaccumulation under different scenarios, and is demonstrated to be robust and identifiable.
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Optimal activation strategy of discrete scanning sensors for fault detection in distributed-parameter systems
Maciej Patan,Dariusz Ucinski +1 more
TL;DR: A general scheme of such an approach leading to maximization of the fault detection efficiency in distributed-parameter systems is delineated and tested via computer simulations regarding an advection-diffusion problem.
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Guaranteed estimation of electrochemical parameters by set inversion using interval analysis
TL;DR: In this article, the bounded-error approach to parameter estimation is applied in the electrochemistry field in order to obtain reliable estimates for kinetic parameters, and a set guaranteed to contain all values of the parameter vector that lead to model outputs consistent with these error bars is computed, based on interval analysis and set inversion.