Model calibration and parameter estimation : for environmental and water resource systems / by Ne-Zheng Sun, Alexander Sun.

Format:

Book

Author/Creator:

Sun, Ne-Zheng, Author.

Sun, Alexander, Author.

Language:

English

Subjects (All):

Mathematical models.

Hydrogeology.

Chemometrics.

Mathematical Modeling and Industrial Mathematics.

Math. Applications in Chemistry.

Local Subjects:

Mathematical Modeling and Industrial Mathematics.

Hydrogeology.

Math. Applications in Chemistry.

Physical Description:

1 online resource (638 p.)

Edition:

1st ed. 2015.

Place of Publication:

New York, NY : Springer New York : Imprint: Springer, 2015.

Language Note:

English

Summary:

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.

Contents:

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.

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

ISBN:

1-4939-2323-4