| bibtype |
J -
Journal Article
|
| ARLID |
0410547 |
| utime |
20240103182221.7 |
| mtime |
20060210235959.9 |
| title
(primary) (eng) |
Indicator space configuration for early warning of violent political conflicts by genetic algorithms |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0250807 |
| ISSN |
0254-5330 |
| title
|
Annals of Operations Research |
| volume_id |
97 |
| volume |
2 (2000) |
| page_num |
287-311 |
| publisher |
|
|
| keyword |
genetic algorithms |
| keyword |
indicator selection |
| keyword |
neural networks |
| author
(primary) |
| ARLID |
cav_un_auth*0212752 |
| name1 |
Ivanova |
| name2 |
Petya |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0212465 |
| name1 |
Tagarev |
| name2 |
T. D. |
| country |
BG |
|
| COSATI |
12B |
| cas_special |
| project |
| project_id |
GA102/99/1564 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0004444 |
|
| research |
AV0Z1075907 |
| abstract
(eng) |
Recognition of preconflict situations has a powerful potential for early warning of violent political conflicts. This paper focuses on the design and application of artificial neural networks as classifiers of preconflict situations. Achieving a desired level of performance of the neural network relies on the appropriate construction of recognition space (selection of indicators) and the choice of network architecture. |
| RIV |
BB |
| department |
AS |
| permalink |
http://hdl.handle.net/11104/0130636 |
| ID_orig |
UTIA-B 20010016 |
| arlyear |
2000 |
| mrcbU63 |
cav_un_epca*0250807 Annals of Operations Research 0254-5330 1572-9338 Roč. 97 č. 2 2000 287 311 Springer |
|