Probabilistic Finite Element Model Updating Using Bayesian Statistics, Marwala Tshilidzi
Автор: Koller Daphne, Friedman Nir Название: Probabilistic Graphical Models: Principles and Techniques ISBN: 0262013193 ISBN-13(EAN): 9780262013192 Издательство: MIT Press Рейтинг: Цена: 21161.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.
Most tasks require a person or an automated system to reason -- to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.
Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.
Автор: Bass Название: Probabilistic Techniques in Analysis ISBN: 0387943870 ISBN-13(EAN): 9780387943879 Издательство: Springer Рейтинг: Цена: 12012.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Exploring the use of techniques drawn from probability research to tackle problems in mathematical analysis, this study includes discussion of the construction of the Martin boundary, Dahlberg`s Theorem, probabilistic proofs of the boundary Harnack principle, and much more.
Автор: Dana Kelly; Curtis Smith Название: Bayesian Inference for Probabilistic Risk Assessment ISBN: 1447127080 ISBN-13(EAN): 9781447127086 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book synthesizes significant recent advances in the use of risk analysis in many government agencies and private corporations, providing a Bayesian foundation for framing probabilistic problems and performing inference on these problems.
Описание: "This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation" Dr.
Автор: Reich Название: Probabilistic Forecasting and Bayesian Data Assimilation ISBN: 1107069394 ISBN-13(EAN): 9781107069398 Издательство: Cambridge Academ Рейтинг: Цена: 19325.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on the Bayesian approach to data assimilation, outlining the subject`s key ideas and concepts, and explaining how to implement specific data assimilation algorithms. It is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.
Автор: Reich Название: Probabilistic Forecasting and Bayesian Data Assimilation ISBN: 1107663911 ISBN-13(EAN): 9781107663916 Издательство: Cambridge Academ Рейтинг: Цена: 7445.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on the Bayesian approach to data assimilation, outlining the subject`s key ideas and concepts, and explaining how to implement specific data assimilation algorithms. It is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.
Автор: Tim Bedford Название: Probabilistic Risk Analysis ISBN: 0521773202 ISBN-13(EAN): 9780521773201 Издательство: Cambridge Academ Рейтинг: Цена: 14731.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Drawing on extensive experience, the authors focus on the conceptual and mathematical foundations underlying the quantification, interpretation and management of risk. They cover standard topics as well as important new subjects such as the use of expert judgement and uncertainty propagation. The relationship with decision making is highlighted.
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