Editor(s): Karny, Miroslav (Academy of Sciences of the Czech Republic, Prague, Czech Republic). Series: Advanced Information and Knowledge Processing. Num Pages: 546 pages, 6 black & white tables, biography. BIC Classification: UFM; UGK; UYQ; UYQP; UYZG. Category: (G) General (US: Trade). Dimension: 235 x 155 x 28. Weight in Grams: 831. . 2014. Paperback. . . . . Books ship from the US and Ireland.

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Detalles bibliogr�ficos

T�tulo: Optimized Bayesian Dynamic Advising
Editor: Springer London Ltd
Fecha de publicaci�n: 2014
Idioma: Ingl�s
ISBN 10: 1447156757
ISBN 13: 9781447156758
Encuadernaci�n: Encuadernaci�n de tapa blanda
Estado: New

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Sinopsis

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.

De la contraportada

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.

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