| bibtype |
J -
Journal Article
|
| ARLID |
0557126 |
| utime |
20240903170555.1 |
| mtime |
20220505235959.9 |
| SCOPUS |
85130701278 |
| WOS |
000795530700002 |
| DOI |
10.14311/NNW.2022.32.002 |
| title
(primary) (eng) |
Modeling of discrete questionnaire data with dimension reduction |
| specification |
| page_count |
27 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0290321 |
| ISSN |
1210-0552 |
| title
|
Neural Network World |
| volume_id |
32 |
| volume |
1 (2022) |
| page_num |
15-41 |
| publisher |
| name |
Ústav informatiky AV ČR, v. v. i. |
|
|
| keyword |
questionnaire data analysis |
| keyword |
dimension reduction |
| keyword |
binomial mixture |
| keyword |
recursive Bayesian mixture estimation |
| keyword |
accident severity |
| author
(primary) |
| ARLID |
cav_un_auth*0412278 |
| name1 |
Jozová |
| name2 |
Šárka |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování signálů |
| full_dept (eng) |
Department of Signal Processing |
| department (cz) |
ZS |
| department (eng) |
ZS |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0383037 |
| name1 |
Uglickich |
| name2 |
Evženie |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování signálů |
| full_dept |
Department of Signal Processing |
| department (cz) |
ZS |
| department |
ZS |
| full_dept |
Department of Signal Processing |
| country |
RU |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101167 |
| name1 |
Nagy |
| name2 |
Ivan |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování signálů |
| full_dept |
Department of Signal Processing |
| department (cz) |
ZS |
| department |
ZS |
| full_dept |
Department of Signal Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0330517 |
| name1 |
Likhonina |
| name2 |
Raissa |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování signálů |
| full_dept |
Department of Signal Processing |
| department (cz) |
ZS |
| department |
ZS |
| full_dept |
Department of Signal Processing |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| source |
|
| cas_special |
| project |
| project_id |
8A19009 |
| agency |
GA MŠk |
| country |
CZ |
| ARLID |
cav_un_auth*0385121 |
|
| abstract
(eng) |
The paper deals with the task of modeling discrete questionnaire data with a reduced dimension of the model. The discrete model dimension is reduced using the construction of local models based on independent binomial mixtures estimated with the help of recursive Bayesian algorithms in the combination with the naive Bayes technique. The main contribution of the paper is a three-phase algorithm of the discrete model dimension reduction, which allows to model high-dimensional questionnaire data with high number of explanatory variables and their possible realizations. The proposed general solution is applied to the traffic accident questionnaire analysis, where it takes the form of the classification of the accident circumstances and prediction of the traffic accident severity using the currently measured discrete data. Results of testing the obtained model on real data and comparison with theoretical counterparts are demonstrated. |
| result_subspec |
WOS |
| RIV |
BB |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10103 |
| reportyear |
2023 |
| num_of_auth |
4 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0331259 |
| confidential |
S |
| mrcbC86 |
n.a. Article Computer Science Artificial Intelligence |
| mrcbC91 |
A |
| mrcbT16-e |
COMPUTERSCIENCEARTIFICIALINTELLIGENCE |
| mrcbT16-j |
0.165 |
| mrcbT16-s |
0.247 |
| mrcbT16-D |
Q4 |
| mrcbT16-E |
Q4 |
| arlyear |
2022 |
| mrcbU14 |
85130701278 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000795530700002 WOS |
| mrcbU56 |
pdf |
| mrcbU63 |
cav_un_epca*0290321 Neural Network World 1210-0552 Roč. 32 č. 1 2022 15 41 Ústav informatiky AV ČR, v. v. i. |
|