| bibtype |
V -
Research Report
|
| ARLID |
0377542 |
| utime |
20240103200943.2 |
| mtime |
20120620235959.9 |
| title
(primary) (eng) |
Application of Sequential Monte Carlo Estimation for Early Phase of Radiation Accident |
| publisher |
| place |
Praha |
| name |
UTIA AV CR, v.v.i |
| pub_time |
2012 |
|
| specification |
| page_count |
25 s. |
| media_type |
pdf |
|
| edition |
| name |
Research Report |
| volume_id |
2322 |
|
| keyword |
radiation protection |
| keyword |
dispersion modeling |
| keyword |
particle filter |
| author
(primary) |
| ARLID |
cav_un_auth*0101207 |
| name1 |
Šmídl |
| name2 |
Václav |
| 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 |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0228606 |
| name1 |
Hofman |
| name2 |
Radek |
| 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. |
|
| source |
|
| cas_special |
| project |
| project_id |
VG20102013018 |
| agency |
GA MV |
| country |
CZ |
| ARLID |
cav_un_auth*0265869 |
|
| abstract
(eng) |
The early phase of radiation accident is characterized by minimum number of measured data and high uncertainty in both atmospheric conditions and radiation situation. Our goal is to provide an accurate method of radiation situation assessment that is capable to respect the uncertainty and provide informative predictions of its evolution for the involved decision makers. We propose a state space model based on atmospheric dispersion model, numerical weather model with local corrections and random walk on the model corrections and release evolution. This model is highly nonlinear and is estimated using sequential Monte Carlo. Since the model is significantly more complex that previously considered models and its estimation with naive proposal densities become too computationally demanding. We propose to construct a proposal density using problem specific simplification followed by application of the Laplace approximation. Properties of the resulting estimation procedure are illustrated on a twin experiment. |
| reportyear |
2013 |
| RIV |
BB |
| num_of_auth |
2 |
| mrcbC52 |
4 O 4o 20231122135103.9 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0209671 |
| arlyear |
2012 |
| mrcbTft |
\nSoubory v repozitáři: 0377542.pdf |
| mrcbU10 |
2012 |
| mrcbU10 |
Praha UTIA AV CR, v.v.i |
|