| bibtype |
J -
Journal Article
|
| ARLID |
0477083 |
| utime |
20240103214403.3 |
| mtime |
20170817235959.9 |
| SCOPUS |
84999791726 |
| WOS |
000404307900001 |
| DOI |
10.1016/j.fss.2016.09.011 |
| title
(primary) (eng) |
On the definition of penalty functions in data aggregation |
| specification |
| page_count |
19 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0256642 |
| ISSN |
0165-0114 |
| title
|
Fuzzy Sets and Systems |
| volume_id |
323 |
| volume |
1 (2017) |
| page_num |
1-18 |
| publisher |
|
|
| keyword |
Aggregation functions |
| keyword |
Averaging aggregation function |
| keyword |
Penalty functions |
| keyword |
Quasi-penalty functions |
| keyword |
Spread measures |
| author
(primary) |
| ARLID |
cav_un_auth*0271524 |
| share |
15 |
| name1 |
Bustince |
| name2 |
H. |
| country |
ES |
| garant |
K |
|
| author
|
| ARLID |
cav_un_auth*0271526 |
| share |
15 |
| name1 |
Beliakov |
| name2 |
G. |
| country |
AU |
|
| author
|
| ARLID |
cav_un_auth*0330395 |
| share |
15 |
| name1 |
Dimuro |
| name2 |
G. P. |
| country |
BR |
|
| author
|
| ARLID |
cav_un_auth*0298830 |
| share |
15 |
| name1 |
Bedregal |
| name2 |
B. |
| country |
BR |
|
| author
|
| ARLID |
cav_un_auth*0101163 |
| full_dept (cz) |
Ekonometrie |
| full_dept |
Department of Econometrics |
| department (cz) |
E |
| department |
E |
| full_dept |
Department of Econometrics |
| share |
40 |
| name1 |
Mesiar |
| name2 |
Radko |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| abstract
(eng) |
In this paper, we point out several problems in the different definitions (and related results) of penalty functions found in the literature. Then, we propose a new standard definition of penalty functions that overcomes such problems. Some results related to averaging aggregation functions, in terms of penalty functions, are presented, as the characterization of averaging aggregation functions based on penalty functions. Some examples are shown, as the penalty functions based on spread measures, which happen to be continuous. We also discuss the definition of quasi-penalty functions, in order to deal with non-monotonic (or weakly/directionally monotonic) averaging functions. |
| RIV |
BA |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10101 |
| reportyear |
2018 |
| num_of_auth |
5 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0274028 |
| confidential |
S |
| mrcbC86 |
1* Article Computer Science Theory Methods|Mathematics Applied|Statistics Probability |
| mrcbC86 |
1* Article Computer Science Theory Methods|Mathematics Applied|Statistics Probability |
| mrcbC86 |
1* Article Computer Science Theory Methods|Mathematics Applied|Statistics Probability |
| mrcbT16-e |
COMPUTERSCIENCETHEORYMETHODS|MATHEMATICSAPPLIED|STATISTICSPROBABILITY |
| mrcbT16-j |
0.639 |
| mrcbT16-s |
1.138 |
| mrcbT16-B |
51.265 |
| mrcbT16-D |
Q2 |
| mrcbT16-E |
Q1 |
| arlyear |
2017 |
| mrcbU14 |
84999791726 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000404307900001 WOS |
| mrcbU63 |
cav_un_epca*0256642 Fuzzy Sets and Systems 0165-0114 1872-6801 Roč. 323 č. 1 2017 1 18 Elsevier |
|