| bibtype |
J -
Journal Article
|
| ARLID |
0481470 |
| utime |
20240103214945.2 |
| mtime |
20171116235959.9 |
| SCOPUS |
85031808792 |
| WOS |
000417659000004 |
| DOI |
10.1016/j.ijar.2017.10.010 |
| title
(primary) (eng) |
A new definition of entropy of belief functions in the Dempster-Shafer theory |
| specification |
| page_count |
17 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0256774 |
| ISSN |
0888-613X |
| title
|
International Journal of Approximate Reasoning |
| volume_id |
92 |
| volume |
1 (2018) |
| page_num |
49-65 |
| publisher |
|
|
| keyword |
Dempster-Shafer theory |
| keyword |
Dempster’s rule of combination |
| keyword |
Plausibility transform |
| author
(primary) |
| ARLID |
cav_un_auth*0101118 |
| full_dept |
Department of Decision Making Theory |
| share |
50 |
| 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 |
| garant |
K |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0275452 |
| name1 |
Shenoy |
| name2 |
P. P. |
| country |
US |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0353269 |
| project_id |
GA15-00215S |
| agency |
GA ČR |
| country |
CZ |
|
| abstract
(eng) |
A new definition of entropy of basic probability assignments in the Dempster–Shafer theory of belief functions is proposed. We state a list of six desired properties of entropy for DS belief functions theory, four of which are motivated by Shannon’s definition of entropy of probability functions, and the remaining two are requirements that adapt this measure to the philosophy of the DS theory. The new definition has two components. The first component is Shannon’s entropy of an equivalent probability mass function obtained using the plausibility transform, which constitutes the conflict measure of entropy. The second component is Dubois-Prade’s definition of entropy of basic probability assignments in the DS theory, which constitutes the non-specificity measure of entropy. |
| RIV |
AH |
| FORD0 |
50000 |
| FORD1 |
50200 |
| FORD2 |
50201 |
| reportyear |
2019 |
| num_of_auth |
2 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0277040 |
| cooperation |
| ARLID |
cav_un_auth*0353454 |
| name |
School of Business, University of Kansas, |
| country |
US |
|
| confidential |
S |
| mrcbC86 |
1* Article Computer Science Artificial Intelligence |
| mrcbT16-e |
COMPUTERSCIENCEARTIFICIALINTELLIGENCE |
| mrcbT16-j |
0.603 |
| mrcbT16-s |
0.606 |
| mrcbT16-B |
43.815 |
| mrcbT16-D |
Q3 |
| mrcbT16-E |
Q2 |
| arlyear |
2018 |
| mrcbU14 |
85031808792 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000417659000004 WOS |
| mrcbU63 |
cav_un_epca*0256774 International Journal of Approximate Reasoning 0888-613X 1873-4731 Roč. 92 č. 1 2018 49 65 Elsevier |
|