Optimized Bayesian Dynamic Advising (Hardcover)

Miroslav Karny

ISBN 10: 1852339284 / ISBN 13: 9781852339289

Verlag: Springer London Ltd, England, 2005

Beschreibung

Hardcover. Written by one of the world?s leading groups in the area of Bayesian identification, control, and decision making, this book provides the theoretical and algorithmic basis of optimized probabilistic advising.Starting from abstract ideas and formulations, and culminating in detailed algorithms, the book comprises a unified treatment of an important problem of the design of advisory systems supporting supervisors of complex processes. It introduces the theoretical and algorithmic basis of developed advising, relying on novel and powerful combination black-box modeling by dynamic mixture models and fully probabilistic dynamic optimization.Written for a broad audience, including developers of algorithms and application engineers, researchers, lecturers, and postgraduates, this book can be used as a reference tool, and an advanced text on Bayesian dynamic decision making. A CD contains a specialized Matlab-based Mixtools toolbox, and examples illustrating the most important and complex areas of the material presented. r Contents 1 Introduction . 1 Motivation . 2 State of the art . 1 Operator supports . 2 Mainstream multivariate techniques . 3 Developed advising and its role in computer support . 10 2 Underlying theory . 1 General conventions . 2 Basic notions and notations . Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Bestandsnummer des Verkäufers 9781852339289

Bibliografische Details

• Titel: Optimized Bayesian Dynamic Advising (Hardcover)
• Verlag: Springer London Ltd, England
• Erscheinungsjahr: 2005
• Sprache: Englisch
• ISBN-10: 1852339284
• ISBN-13: 9781852339289
• Einband: Hardcover
• Zustand: new

Über diesen Titel

Inhaltsangabe

A state-of-the-art research monograph providing consistent treatment of supervisory control, by one of the world’s leading groups in the area of Bayesian identification, control, and decision making.

Von der hinteren Coverseite

Written by one of the world s leading groups in the area of Bayesian identification, control and decision making, this book provides the theoretical and algorithmic basis of optimized probabilistic advising.
Starting from abstract ideas and formulations, and culminating in detailed algorithms, Optimized Bayesian Dynamic Advising comprises a unified treatment of an important problem of the design of advisory systems supporting supervisors of complex processes. It introduces the theoretical and algorithmic basis of developed advising, relying on novel and powerful combination black-box modeling by dynamic mixture models and fully probabilistic dynamic optimization. The proposed non-standard problem formulation and its solution mark a significant contribution to the design of anthropocentric automation systems.
Written for a broad audience, including developers of algorithms and application engineers, researchers, lecturers and postgraduates, this book can be used as a reference tool, and an advanced text on Bayesian dynamic decision making.