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Model calibration and parameter esti...
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Sun, Alexander.
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Model calibration and parameter estimation = for environmental and water resource systems /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Model calibration and parameter estimation/ by Ne-Zheng Sun, Alexander Sun.
其他題名:
for environmental and water resource systems /
作者:
Sun, Ne-Zheng.
其他作者:
Sun, Alexander.
出版者:
New York, NY :Springer New York : : 2015.,
面頁冊數:
xxviii, 621 p. :ill. (some col.), digital ;24 cm.
內容註:
Introduction -- The Classical Inverse Problem -- The Gauss-Newton Method -- Multiobjective Inversion and Regularization -- Statistical Methods for Parameter Estimation -- Model Differentiation -- Model Dimension Reduction -- Development of Data-Driven Models -- Data Assimilation for Inversion -- Model Uncertainty Quantification -- Optimal Experimental Design -- Goal-Oriented Modeling.
Contained By:
Springer eBooks
標題:
Mathematical models. -
電子資源:
http://dx.doi.org/10.1007/978-1-4939-2323-6
ISBN:
9781493923236 (electronic bk.)
Model calibration and parameter estimation = for environmental and water resource systems /
Sun, Ne-Zheng.
Model calibration and parameter estimation
for environmental and water resource systems /[electronic resource] :by Ne-Zheng Sun, Alexander Sun. - New York, NY :Springer New York :2015. - xxviii, 621 p. :ill. (some col.), digital ;24 cm.
Introduction -- The Classical Inverse Problem -- The Gauss-Newton Method -- Multiobjective Inversion and Regularization -- Statistical Methods for Parameter Estimation -- Model Differentiation -- Model Dimension Reduction -- Development of Data-Driven Models -- Data Assimilation for Inversion -- Model Uncertainty Quantification -- Optimal Experimental Design -- Goal-Oriented Modeling.
This three-part book provides a comprehensive and systematic introduction to the development of useful models for complex systems. Part 1 covers the classical inverse problem for parameter estimation in both deterministic and statistical frameworks, Part 2 is dedicated to system identification, hyperparameter estimation, and model dimension reduction, and Part 3 considers how to collect data and construct reliable models for prediction and decision-making. For the first time, topics such as multiscale inversion, stochastic field parameterization, level set method, machine learning, global sensitivity analysis, data assimilation, model uncertainty quantification, robust design, and goal-oriented modeling, are systematically described and summarized in a single book from the perspective of model inversion, and elucidated with numerical examples from environmental and water resources modeling. Readers of this book will not only learn basic concepts and methods for simple parameter estimation, but also get familiar with advanced methods for modeling complex systems. Algorithms for mathematical tools used in this book, such as numerical optimization, automatic differentiation, adaptive parameterization, hierarchical Bayesian, metamodeling, Markov chain Monte Carlo, are covered in details. This book can useful for graduate and upper level undergraduate students majoring in environmental engineering, hydrology, and geosciences. It also serves as an essential reference book for petroleum engineers, mining engineers, chemists, mechanical engineers, ecologists, biomedical engineers, applied mathematicians, and others who perform mathematical modeling.
ISBN: 9781493923236 (electronic bk.)
Standard No.: 10.1007/978-1-4939-2323-6doiSubjects--Topical Terms:
522882
Mathematical models.
LC Class. No.: QA401
Dewey Class. No.: 003.3
Model calibration and parameter estimation = for environmental and water resource systems /
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Introduction -- The Classical Inverse Problem -- The Gauss-Newton Method -- Multiobjective Inversion and Regularization -- Statistical Methods for Parameter Estimation -- Model Differentiation -- Model Dimension Reduction -- Development of Data-Driven Models -- Data Assimilation for Inversion -- Model Uncertainty Quantification -- Optimal Experimental Design -- Goal-Oriented Modeling.
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