20 papers · ranked by Valyu relevance
Christoph Schranz, Paul D Docherty, Yeong Shiong Chiew, Knut Möller + 1 more
'J Geoffrey Chase'] Background Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual’s model parameter values must be identified with information available at the bedside.…
Hong Qin
Parameter identification is an important branch of automatic control. Due to its special function, it has been widely used in various fields, especially the modeling of complex systems or systems whose parameters are not easy to determine. With the development of control technology, the scale of the control object is…
Jan Hinrichsen, Nina Reiter, Lars Bräuer, Friedrich Paulsen + 2 more
The identification of material parameters accurately describing the region-dependent mechanical behavior of human brain tissue is crucial for computational models used to assist, e.g., the development of safety equipment like helmets or the planning and execution of brain surgery. While the division of the human brain…
Shun Wang, Wenrui Hao
Practical identifiability is a critical concern in data-driven modeling of mathematical systems. In this paper, we propose a novel framework for practical identifiability analysis to evaluate parameter identifiability in mathematical models of biological systems. Starting with a rigorous mathematical definition of…
Syed Murtuza Baker, C Hart Poskar, Falk Schreiber, Björn H Junker
Background Utilizing kinetic models of biological systems commonly require computational approaches to estimate parameters, posing a variety of challenges due to their highly non-linear and dynamic nature, which is further complicated by the issue of non-identifiability. We propose a novel parameter estimation…
Krishnan Srinivasarengan, José Ragot, Christophe Aubrun, Didier Maquin
'Didier Maquin'] In several model-based system maintenance problems, parameters are used to represent unknown characteristics of a component, equipment degradation, etc. This allows for modelling constant, slow-varying terms. The identifiability of these parameters is an important condition to estimate them. Linear…
Linda Wanika, Joseph R. Egan, Nivedhitha Swaminathan, Carlos A. Duran-Villalobos + 3 more
Advancements in digital technology have brought modelling to the forefront in many disciplines from healthcare to architecture. Mathematical models, often represented using parametrised sets of ordinary differential equations, can be used to characterise different processes. To infer possible estimates for the unknown…
Harry Saxton, Xu Xu, Torsten Schenkel, Richard H. Clayton + 1 more
Dynamical system models typically involve numerous input parameters whose “effects” and orthogonality need to be quantified through sensitivity analysis, to identify inputs contributing the greatest uncertainty. Whilst prior art has compared total-order estimators’ role in recovering “true” effects, assessing their…
Authors not listed
Developing a transferable classical force field (FF) has historically been a lengthy, expert-informed process. In this work, we integrate optimization, machine learning, and data science techniques to accelerate the systematic design and parameterization of transferable FF models. As a demonstration, we create…
David L. I. Janzén, Linnéa Bergenholm, Mats Jirstrand, Joanna Parkinson + 3 more
'Joanna Parkinson' 'James Yates' 'Neil D. Evans' 'Michael J. Chappell'] Issues of parameter identifiability of routinely used pharmacodynamics models are considered in this paper. The structural identifiability of 16 commonly applied pharmacodynamic model structures was analyzed analytically, using the input-output…
Alex Borisevich
The article gives an overview of the parameter numerical continuation methodology applied to setpoint control and parameter identification of nonlinear systems. The control problems for affine systems as well as general (nonaffine) nonlinear systems are considered. Online parameter identification is also presented in…
Pu Li, Quoc Dong Vu
Background Parameter estimation represents one of the most significant challenges in systems biology. This is because biological models commonly contain a large number of parameters among which there may be functional interrelationships, thus leading to the problem of non-identifiability. Although identifiability…
M. J. Colebank, N.C. Chesler
In-vivo studies of pulmonary hypertension (PH) have provided key insight into the progression of the disease and right ventricular (RV) dysfunction. Additional in-silico experiments using multiscale computational models have provided further details into biventricular mechanics and hemodynamic function in the presence…
Son-Il Kwak, Gang Choe, In-Song Kim, Gyong-Ho Jo + 1 more
- To improve the effectiveness of the fuzzy identification, a structure identification method based on moving rate is proposed for T-S fuzzy model. The proposed method is called "T-S modeling (or T-S fuzzy identification method) based on moving rate". First, to improve the shortcomings of existing fuzzy reasoning…
Jessica R. Conrad, Marisa C. Eisenberg
identifiability Authors: ['Jessica R. Conrad' 'Marisa C. Eisenberg'] - We provide an alternative method to constrain existing models using novel input data streams - The structural identifiability of nonlinear ODE models is not worsened with the introduction of a forcing input function (new data stream) - The inclusion…
Prem Jagadeesan, Karthik Raman, Arun K Tangirala
Computational modelling of biological processes poses multiple challenges in each stage of the modelling exercise. Some significant challenges include identifiability, precisely estimating parameters from limited data, informative experiments and anisotropic sensitivity in the parameter space. One of these challenges’…
Milena Rmus, Ti-Fen Pan, Liyu Xia, Anne G. E. Collins
Computational cognitive models have been used extensively to formalize cognitive processes. Model parameters offer a simple way to quantify individual differences in how humans process information. Similarly, model comparison allows researchers to identify which theories, embedded in different models, provide the best…
Authors not listed
We implemented a straight-forward algorithm for generating a list of potential molecular fragments from a given molecule by simulating sequential fracturing of single bonds; we refer to this approach as the Simulated Sequential Single-Bond-Breaking (3S2B) algorithm. Applying the algorithm to a list of chemical…
Authors not listed
Identification of unknown compounds in complex mixtures is a difficult, time consuming and challenging problem in several areas of chemistry. High-performance liquid chromatography (HPLC) coupled to tandem mass spectrometry (MS2) based on collision-activated dissociation (CAD) is a standard approach used to identify…
Ulrich Pabst
The idea of peptide mass fingerprinting (PMF) was first introduced in 1989, when protein research was facing a serious issue with automated Edman-degradation taking nearly one hour per reaction cycle. There was a dire need for more streamlined and fast ways to analyse proteins and peptides. Since the first steps…