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Titlebook: Model Calibration and Parameter Estimation; For Environmental an Ne-Zheng Sun,Alexander Sun Book 2015 Springer Science+Business Media, LLC

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书目名称Model Calibration and Parameter Estimation
副标题For Environmental an
编辑Ne-Zheng Sun,Alexander Sun
视频video
概述Various hydrological models are described and classified.Summarizes the state-of-the-art developments in this subject area that can bring the readers to the front of knowledge.Synthetic examples and r
图书封面Titlebook: Model Calibration and Parameter Estimation; For Environmental an Ne-Zheng Sun,Alexander Sun Book 2015 Springer Science+Business Media, LLC
描述This three-part book provides a comprehensive and systematic introduction to these challenging topics such as model calibration, parameter estimation, reliability assessment, and data collection design. 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 bo
出版日期Book 2015
关键词Forward Problems; Inverse Problems; Mathematical Modeling; Model Calibration and Parameter Estimation; S
版次1
doihttps://doi.org/10.1007/978-1-4939-2323-6
isbn_softcover978-1-4939-4092-9
isbn_ebook978-1-4939-2323-6
copyrightSpringer Science+Business Media, LLC 2015
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The Hyper System: Knowledge Reformation for Efficient First-Order Hypothetical Reasoningw that knowledge reformation allows low-order polynomial time inference to find a near-optimal solution in cost-based first-order hypothetical reasoning (or ‘abduction’) problems. We will also present experimental results that confirm the effectiveness of our compilation method.
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