| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0598807 |
| utime |
20241010094640.6 |
| mtime |
20241001235959.9 |
| DOI |
10.1007/978-3-031-65993-5_23 |
| title
(primary) (eng) |
Entropy-Based Search for the Most Informative Belief Functions |
| specification |
| page_count |
8 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0598452 |
| ISBN |
978-3-031-65992-8 |
| ISSN |
2194-5357 |
| title
|
Combining, Modelling and Analyzing Imprecision, Randomness and Dependence |
| page_num |
192-199 |
| publisher |
| place |
Cham |
| name |
Springer |
| year |
2024 |
|
|
| keyword |
belief functions |
| keyword |
entropy |
| keyword |
information content |
| author
(primary) |
| ARLID |
cav_un_auth*0101118 |
| name1 |
Jiroušek |
| name2 |
Radim |
| institution |
UTIA-B |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept (eng) |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department (eng) |
MTR |
| full_dept |
Department of Decision Making Theory |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0216188 |
| name1 |
Kratochvíl |
| name2 |
Václav |
| institution |
UTIA-B |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department |
MTR |
| full_dept |
Department of Decision Making Theory |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| source |
|
| cas_special |
| project |
| project_id |
GA21-07494S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0430801 |
|
| abstract
(eng) |
The paper deals with the problem studied in our previous paper published in Int. J. Approx. Reasoning, which raised new questions rather than brought solutions. Thus, the current contribution also tries to answer the ever-lasting question: Which belief function entropies described in the literature can detect optimal models? Nevertheless, here, we approach the problem differently. We try to find out the entropy functions that are indirectly proportional to the informative content of belief functions, i.e., the moreinformative the belief function, the lower its entropy. |
| action |
| ARLID |
cav_un_auth*0472961 |
| name |
International Conference on Soft Methods in Probability and Statistics 2024 - SMPS 2024 /11./ |
| dates |
20240903 |
| mrcbC20-s |
20240906 |
| place |
Salzburg |
| country |
AT |
|
| RIV |
BA |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10102 |
| reportyear |
2025 |
| num_of_auth |
2 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0356718 |
| confidential |
S |
| arlyear |
2024 |
| mrcbU14 |
SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0598452 Combining, Modelling and Analyzing Imprecision, Randomness and Dependence Springer 2024 Cham 192 199 978-3-031-65992-8 Advances in Intelligent Systems and Computing 2194-5357 |
|