Item type | Current location | Collection | Call number | Copy number | Status | Date due | Barcode |
---|---|---|---|---|---|---|---|
E-Books | Biblioteca da FCTUNL Online | Não Ficção | QA401.SPR FCT 96585 (Browse shelf) | 1 | Available |
Browsing Biblioteca da FCTUNL Shelves , Shelving location: Online , Collection code: Não Ficção Close shelf browser
No cover image available | ||||||||
QA401.SPR FCT 81567 Mathematical modeling in economics, ecology and the environment | QA401.SPR FCT 82441 Coping with complexity | QA401.SPR FCT 96549 Mathematical models of viscous friction | QA401.SPR FCT 96585 Model calibration and parameter estimation | QA401.SPR FCT 98135 Volume conjecture for knots | QA401.SPR FCT 98210 Approximation theory and algorithms for data analysis | QA401. SPR FCT 98291 New trends in approximation theory |
Colocação: Online
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.
There are no comments for this item.