bibtype |
V -
Research Report
|
ARLID |
0315659 |
utime |
20240111140710.9 |
mtime |
20081202235959.9 |
title
(primary) (eng) |
Fully probabilistic knowledge expression and incorporation |
publisher |
place |
Milano |
name |
Istituto di Matematica Applicata e Tecnologie Informatiche |
pub_time |
2008 |
|
specification |
page_count |
28 s. |
media_type |
www |
|
edition |
name |
Research Report-Istituto di Matematica Applicata e Tecnologie Informatiche |
volume_id |
8-10MI |
|
keyword |
Bayesian estimation |
keyword |
prior knowledge |
keyword |
automatised knowledge elicitation |
author
(primary) |
ARLID |
cav_un_auth*0101124 |
name1 |
Kárný |
name2 |
Miroslav |
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*0101061 |
name1 |
Andrýsek |
name2 |
Josef |
institution |
UTIA-B |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0205835 |
name1 |
Bodini |
name2 |
A. |
country |
IT |
|
author
|
ARLID |
cav_un_auth*0101092 |
name1 |
Guy |
name2 |
Tatiana Valentine |
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*0101138 |
name1 |
Kracík |
name2 |
Jan |
institution |
UTIA-B |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0101168 |
name1 |
Nedoma |
name2 |
Petr |
institution |
UTIA-B |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
author
|
ARLID |
cav_un_auth*0205836 |
name1 |
Ruggeri |
name2 |
F. |
country |
IT |
|
source |
|
cas_special |
project |
project_id |
1M0572 |
agency |
GA MŠk |
ARLID |
cav_un_auth*0001814 |
|
project |
project_id |
2C06001 |
agency |
GA MŠk |
ARLID |
cav_un_auth*0217685 |
|
project |
project_id |
GA102/08/0567 |
agency |
GA ČR |
ARLID |
cav_un_auth*0239566 |
|
research |
CEZ:AV0Z10750506 |
abstract
(eng) |
Exploitation of prior knowledge in parameter estimation is vital whenever data is not informative enough. Elicitation and quantification of prior knowledge is a well-elaborated art in social and medical appliations but not in engineering ones. Frequently required involvment of a facilitator is mostly unrealistic due to either facilitators' high costs or the high complexitu of modelled relationships that cannot be grasped by the human. This paper provides a facilitator-free approach exploiting a methodology of knowledge sharing. The considered task assumes prospective models be indexed by an unknown finite-dimensional parameter. The parameter is estimated using (i) observed data; (ii) a prior probability density function (pdf); and (iii) uncertain expert's information on the modelled data. The parametric model specifies pdf of the system's output conditioned on realised data and parameter. |
reportyear |
2009 |
RIV |
BB |
mrcbC52 |
4 O 4o 20231122133745.9 |
permalink |
http://hdl.handle.net/11104/0165800 |
arlyear |
2008 |
mrcbTft |
\nSoubory v repozitáři: 0315659.pdf |
mrcbU10 |
2008 |
mrcbU10 |
Milano Istituto di Matematica Applicata e Tecnologie Informatiche |
mrcbU56 |
textovy soubor |
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