Model Based Parameter Estimation: Theory and Applications: Contributions in Mathematical and Computational Sciences, cartea 4
Editat de Hans Georg Bock, Thomas Carraro, Willi Jäger, Stefan Körkel, Rolf Rannacher, Johannes P. Schlöderen Limba Engleză Paperback – 7 mar 2015
The use of scientific computing to model, simulate, and optimize complex processes has become a standard methodology in many scientific fields, as well as in industry. Demonstrating that the use of state-of-the-art optimization techniques in a number of research areas has much potential for improvement, this book provides advanced numerical methods and the very latest results for the applications under consideration.
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Specificații
ISBN-13: 9783642440762
ISBN-10: 3642440762
Pagini: 346
Ilustrații: X, 334 p. 83 illus., 26 illus. in color.
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.49 kg
Ediția:2013
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Contributions in Mathematical and Computational Sciences
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642440762
Pagini: 346
Ilustrații: X, 334 p. 83 illus., 26 illus. in color.
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.49 kg
Ediția:2013
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Contributions in Mathematical and Computational Sciences
Locul publicării:Berlin, Heidelberg, Germany
Cuprins
Parameter Estimation and Optimum Experimental Design for Differential Equation Models: H.G. Bock, St. Körkel, J.P. Schlöder.- Adaptive Finite Element Methods for Parameter Identification Problems: B. Vexler.- Gauss-Newton Methods for Robust Parameter Estimation: T. Binder, E. Kostina.- An Optimal Scanning Sensor Activation Policy for Parameter Estimation of Distributed Systems: D. Ucínski.- Interaction between Experiment, Modeling and Simulation of Spatial Aspects in the JAK2/STAT5 Signaling Pathway: E. Friedmann, A. C. Pfeifer, R. Neumann, U. Klingmüller , R. Rannacher.- The Importance and Challenges of Bayesian Parameter Learning in Systems Biology: J. Mazur, L. Kaderali.- Experiment Setups and Parameter Estimation in Fluorescence Recovery After Photobleaching Experiments: A Review of Current Practice: J. Beaudouin, M. S. Mommer, H. G. Bock, R. Eils.- Drug Resistance in Infectious Diseases: Modeling, Parameter Estimation and Numerical Simulation: Le Thi Thanh An, W. Jäger.- Mathematical Models of Hematopoietic Reconstitution after Stem Cell Transplantation: A. Marciniak-Czochra, Th. Stiehl.- Combustion Chemistry and Parameter Estimation: M. Fischer, U. Riedel.- Numerical Simulation of Catalytic Reactors by Molecular-Based Models: O. Deutschmann, St. Tischer.- Model-Based Design of Experiments for Estimating Heat-Transport Parameters in Tubular Reactors: A.Badinski, D. Corbett.- Parameter Estimation for a Reconstructed SOFC Mixed-Conducting LSCF-Cathode: Th. Carraro, J. Joos.- An Application of Robust Parameter Estimation in Environmental Physics: G. Herzog, F. R. Vogel.- Parameter Estimation in Image Processing and Computer Vision: Ch. S. Garbe, B. Ommer.
Textul de pe ultima copertă
This judicious selection of articles combines mathematical and numerical methods to apply parameter estimation and optimum experimental design in a range of contexts. These include fields as diverse as biology, medicine, chemistry, environmental physics, image processing and computer vision. The material chosen was presented at a multidisciplinary workshop on parameter estimation held in 2009 in Heidelberg. The contributions show how indispensable efficient methods of applied mathematics and computer-based modeling can be to enhancing the quality of interdisciplinary research.
The use of scientific computing to model, simulate, and optimize complex processes has become a standard methodology in many scientific fields, as well as in industry. Demonstrating that the use of state-of-the-art optimization techniques in a number of research areas has much potential for improvement, this book provides advanced numerical methods and the very latest results for the applications under consideration.
The use of scientific computing to model, simulate, and optimize complex processes has become a standard methodology in many scientific fields, as well as in industry. Demonstrating that the use of state-of-the-art optimization techniques in a number of research areas has much potential for improvement, this book provides advanced numerical methods and the very latest results for the applications under consideration.
Caracteristici
Overview of state-of-the-art methods for model based parameter estimation Applications for several scientific disciplines: biology, medicine, chemistry, electrochemistry, environmental physics, image processing and computer vision Parameter estimation is a key feature of computational modelling ? Includes supplementary material: sn.pub/extras