bibtype J - Journal Article
ARLID 0438275
utime 20240103205422.8
mtime 20150107235959.9
SCOPUS 84920065538
WOS 000348624200008
DOI 10.4310/SII.2014.v7.n4.a7
title (primary) (eng) Fully probabilistic knowledge expression and incorporation
specification
page_count 13 s.
media_type P
serial
ARLID cav_un_epca*0362603
ISSN 1938-7989
title Statistics and its Interface
volume_id 7
volume 4 (2014)
page_num 503-515
keyword Bayesian estimation
keyword knowledge elicitation
keyword just-in-time modelling
keyword controlled autoregressive model
author (primary)
ARLID cav_un_auth*0101124
name1 Kárný
name2 Miroslav
full_dept (cz) Adaptivní systémy
full_dept (eng) Department of Adaptive Systems
department (cz) AS
department (eng) AS
institution UTIA-B
full_dept Department of Adaptive Systems
share 20
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101092
name1 Guy
name2 Tatiana Valentine
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
share 20
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0312291
name1 Kracík
name2 J.
country CZ
share 20
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
share 20
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0205835
name1 Bodini
name2 A.
country IT
share 10
author
ARLID cav_un_auth*0205836
name1 Ruggeri
name2 F.
country IT
share 10
source
url http://library.utia.cas.cz/separaty/2014/AS/karny-0438275.pdf
cas_special
project
project_id GA13-13502S
agency GA ČR
ARLID cav_un_auth*0292725
abstract (eng) An exploitation of prior knowledge in parameter estimation becomes vital whenever measured data is not informative enough. Elicitation of quantified prior knowledge is a well-elaborated art in societal and medical applications but not in the engineering ones. Frequently required involvement of a facilitator is mostly unrealistic due to either facilitator’s high costs or complexity of modelled relationships that cannot be grasped by humans. This paper provides a facilitator-free approach based on an advanced knowledgesharing methodology. It presents the approach on commonly available types of knowledge and applies the methodology to a normal controlled autoregressive model.
reportyear 2015
RIV BB
num_of_auth 6
mrcbC52 4 A 4a 20231122140733.1
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0242028
cooperation
ARLID cav_un_auth*0312054
institution VSB
name Technical University Ostrava
country CZ
cooperation
ARLID cav_un_auth*0312055
institution IMATI
name Istituto di Matematica Applicata e Tecnologie Informatiche
country IT
confidential S
mrcbT16-e MATHEMATICALCOMPUTATIONALBIOLOGY|MATHEMATICSINTERDISCIPLINARYAPPLICATIONS
mrcbT16-j 1.057
mrcbT16-s 0.478
mrcbT16-4 Q3
mrcbT16-B 74.395
mrcbT16-C 90.271
mrcbT16-D Q2
mrcbT16-E Q3
arlyear 2014
mrcbTft \nSoubory v repozitáři: karny-0438275.pdf
mrcbU14 84920065538 SCOPUS
mrcbU34 000348624200008 WOS
mrcbU63 cav_un_epca*0362603 Statistics and its Interface 1938-7989 1938-7997 Roč. 7 č. 4 2014 503 515