Probabilistic advisory systems for data-intensive applications

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SYSNO ASEP	0391797
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	Probabilistic advisory systems for data-intensive applications
Author(s)	Quinn, A. (IR) Ettler, P. (CZ) Jirsa, Ladislav (UTIA-B)_RID Nagy, I. (CZ) Nedoma, Petr (UTIA-B)
Source Title	International Journal of Adaptive Control and Signal Processing. - : Wiley - ISSN 0890-6327 Roč. 17, č. 2 (2003), s. 133-148
Number of pages	16 s.
Language	eng - English
Country	GB - United Kingdom
Keywords	mixture od dynamic models ; Bayesian inference ; control design
Subject RIV	BC - Control Systems Theory
R&D Projects	IBS1075102 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR)
CEZ	AV0Z1075907 - UTIA-B
UT WOS	000182339400005
DOI	https://doi.org/10.1002/acs.743
Annotation	The paper deals with mixture modelling as a tool for estimation and control of real-world, multidimensional, dynamic, non-linear processes. The experience gained under the EU project ProDaCTool, in designing and implementing advisory systems in urban traffic regulation, therapy recommendations in nuclear medicine and operator support for metal-strip rolling mill are presented.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2014

Number of the records: 1