Model based parameter estimation (40 resultados)

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Condición: New.

Condición: New. In English.

Condición: New. In English.

Taschenbuch. Condición: Neu. Physically based parameter estimation methods for hydrological models | Revised calibration and application procedures for the Pitman monthly rainfall-runoff model in southern African basins | Evison Kapangaziwiri | Taschenbuch | 188 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844387377 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

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Condición: New. pp. 346.

Hardback. Condición: New. Computational electromagnetics (CEM) involves modeling the interaction of electromagnetic fields with physical objects and their environment, such as the radiation emitted by antennas and the fields scattered from radar targets. First-principles or generating models (GMs) based on Maxwell's equations, provide a microscopic, spatial description of the charge and current distributions that normally require several samples per wavelength. Model-based parameter estimation (MBPE) uses a macroscopic, reduced-order, physically based fitting model (FM) to adaptively sample GM results while minimizing the number needed to quantify various EM observables such as frequency responses, far-field radiation patterns, interaction effects, etc. The FMs can reduce the needed GM sampling cost by a factor of 10 or more while yielding a continuous result of needed observables to avoid missing important details. The FMs can also indicate the numerical uncertainty of such quantities from measured as well as computed data. After an introduction to the subject and its mathematical background, subsequent chapters cover system identification, MBPE techniques and the various roles of Prony's methods as FMs in CEM. Other related topics that are covered include derivative sampling, radiation pattern synthesis and estimation, and assorted other applications. The book is aimed at the computational electromagnetics community and those working in applied sciences with complex models such as acoustics, mechanical structures, geo-physics and physics. …

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Condición: New. pp. 346.

HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Hardcover. Condición: Brand New. 2013 edition. 344 pages. 9.50x6.50x1.00 inches. In Stock.

Taschenbuch. Condición: Neu. Model Based Parameter Estimation | Theory and Applications | Hans Georg Bock (u. a.) | Taschenbuch | Contributions in Mathematical and Computational Sciences | x | Englisch | 2015 | Springer | EAN 9783642440762 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Hardback. Condición: New. Computational electromagnetics (CEM) involves modeling the interaction of electromagnetic fields with physical objects and their environment, such as the radiation emitted by antennas and the fields scattered from radar targets. First-principles or generating models (GMs) based on Maxwell's equations, provide a microscopic, spatial description of the charge and current distributions that normally require several samples per wavelength. Model-based parameter estimation (MBPE) uses a macroscopic, reduced-order, physically based fitting model (FM) to adaptively sample GM results while minimizing the number needed to quantify various EM observables such as frequency responses, far-field radiation patterns, interaction effects, etc. The FMs can reduce the needed GM sampling cost by a factor of 10 or more while yielding a continuous result of needed observables to avoid missing important details. The FMs can also indicate the numerical uncertainty of such quantities from measured as well as computed data. After an introduction to the subject and its mathematical background, subsequent chapters cover system identification, MBPE techniques and the various roles of Prony's methods as FMs in CEM. Other related topics that are covered include derivative sampling, radiation pattern synthesis and estimation, and assorted other applications. The book is aimed at the computational electromagnetics community and those working in applied sciences with complex models such as acoustics, mechanical structures, geo-physics and physics. …

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Hardcover. Condición: Brand New. 350 pages. 9.22x6.15x9.21 inches. In Stock.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. …

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. …

Hardback. Condición: New. Computational electromagnetics (CEM) involves modeling the interaction of electromagnetic fields with physical objects and their environment, such as the radiation emitted by antennas and the fields scattered from radar targets. First-principles or generating models (GMs) based on Maxwell's equations, provide a microscopic, spatial description of the charge and current distributions that normally require several samples per wavelength. Model-based parameter estimation (MBPE) uses a macroscopic, reduced-order, physically based fitting model (FM) to adaptively sample GM results while minimizing the number needed to quantify various EM observables such as frequency responses, far-field radiation patterns, interaction effects, etc. The FMs can reduce the needed GM sampling cost by a factor of 10 or more while yielding a continuous result of needed observables to avoid missing important details. The FMs can also indicate the numerical uncertainty of such quantities from measured as well as computed data. After an introduction to the subject and its mathematical background, subsequent chapters cover system identification, MBPE techniques and the various roles of Prony's methods as FMs in CEM. Other related topics that are covered include derivative sampling, radiation pattern synthesis and estimation, and assorted other applications. The book is aimed at the computational electromagnetics community and those working in applied sciences with complex models such as acoustics, mechanical structures, geo-physics and physics. …

Hardcover. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Paperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Hardback. Condición: New. Computational electromagnetics (CEM) involves modeling the interaction of electromagnetic fields with physical objects and their environment, such as the radiation emitted by antennas and the fields scattered from radar targets. First-principles or generating models (GMs) based on Maxwell's equations, provide a microscopic, spatial description of the charge and current distributions that normally require several samples per wavelength. Model-based parameter estimation (MBPE) uses a macroscopic, reduced-order, physically based fitting model (FM) to adaptively sample GM results while minimizing the number needed to quantify various EM observables such as frequency responses, far-field radiation patterns, interaction effects, etc. The FMs can reduce the needed GM sampling cost by a factor of 10 or more while yielding a continuous result of needed observables to avoid missing important details. The FMs can also indicate the numerical uncertainty of such quantities from measured as well as computed data. After an introduction to the subject and its mathematical background, subsequent chapters cover system identification, MBPE techniques and the various roles of Prony's methods as FMs in CEM. Other related topics that are covered include derivative sampling, radiation pattern synthesis and estimation, and assorted other applications. The book is aimed at the computational electromagnetics community and those working in applied sciences with complex models such as acoustics, mechanical structures, geo-physics and physics. …

Buch. Condición: Neu. Neuware - Computational electromagnetics (CEM) involves modeling the interaction of electromagnetic fields with physical objects and their environment, such as the radiation emitted by antennas and the fields scattered from radar targets. First-principles or generating models (GMs) based on Maxwell's equations, provide a microscopic, spatial description of the charge and current distributions that normally require several samples per wavelength. Model-based parameter estimation (MBPE) uses a macroscopic, reduced-order, physically based fitting model (FM) to adaptively sample GM results while minimizing the number needed to quantify various EM observables such as frequency responses, far-field radiation patterns, interaction effects, etc. The FMs can reduce the needed GM sampling cost by a factor of 10 or more while yielding a continuous result of needed observables to avoid missing important details. The FMs can also indicate the numerical uncertainty of such quantities from measured as well as computed data. After an introduction to the subject and its mathematical background, subsequent chapters cover system identification, MBPE techniques and the various roles of Prony's methods as FMs in CEM. Other related topics that are covered include derivative sampling, radiation pattern synthesis and estimation, and assorted other applications. The book is aimed at the computational electromagnetics community and those working in applied sciences with complex models such as acoustics, mechanical structures, geo-physics and physics.…

Condición: new. Questo è un articolo print on demand.

Condición: new. Questo è un articolo print on demand.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Reliable quantification of available water resources is an important prerequisite for sustainable management and development. However, the data required for adequate resource estimation are usually not available due to inadequate and shrinking measurement networks. Hydrologic models are the standard tool used to generate continuous estimates of stream flow and regionalisation has been the traditional approach to model application in poorly gauged basins. The classical approach to regionalization is to calibrate against naturalized observed data, identify hydrologically similar basins, and then transfer calibrated parameter sets to the ungauged basins. One of the problems related to this approach is the relatively few basins for calibration in southern Africa (due to data quality and availability problems), resulting in huge uncertainties in the prediction process. This study proposes an a priori process to directly estimate parameters of the Pitman monthly rainfall runoff model based on physical basin characteristics. The approach is tested on selected basins in southern African.…