bibtype J - Journal Article
ARLID 0391797
utime 20240103202504.2
mtime 20130417235959.9
WOS 000182339400005
DOI 10.1002/acs.743
title (primary) (eng) Probabilistic advisory systems for data-intensive applications
specification
page_count 16 s.
serial
ARLID cav_un_epca*0256772
ISSN 0890-6327
title International Journal of Adaptive Control and Signal Processing
volume_id 17
volume 2 (2003)
page_num 133-148
publisher
name Wiley
keyword mixture od dynamic models
keyword Bayesian inference
keyword control design
author (primary)
ARLID cav_un_auth*0213041
name1 Quinn
name2 A.
country IR
author
ARLID cav_un_auth*0212695
name1 Ettler
name2 P.
country CZ
author
ARLID cav_un_auth*0101119
name1 Jirsa
name2 Ladislav
full_dept (cz) Adaptivní systémy
full_dept Department of Adaptive Systems
department (cz) AS
department AS
institution UTIA-B
full_dept Department of Adaptive Systems
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0213012
name1 Nagy
name2 I.
country CZ
author
ARLID cav_un_auth*0101168
name1 Nedoma
name2 Petr
full_dept (cz) Adaptivní systémy
full_dept Department of Adaptive Systems
department (cz) AS
department AS
institution UTIA-B
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
cas_special
project
project_id IBS1075102
agency GA AV ČR
country CZ
ARLID cav_un_auth*0014060
research CEZ:AV0Z1075907
abstract (eng) 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.
reportyear 2014
RIV BC
permalink http://hdl.handle.net/11104/0220791
arlyear 2003
mrcbU34 000182339400005 WOS
mrcbU63 cav_un_epca*0256772 International Journal of Adaptive Control and Signal Processing 0890-6327 1099-1115 Roč. 17 č. 2 2003 133 148 Wiley