| bibtype |
J -
Journal Article
|
| ARLID |
0458801 |
| utime |
20240103212148.4 |
| mtime |
20160419235959.9 |
| SCOPUS |
84963861009 |
| WOS |
000373948000002 |
| DOI |
10.1109/TFUZZ.2015.2453020 |
| title
(primary) (eng) |
Preaggregation Functions: Construction and an Application |
| specification |
| page_count |
13 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0253234 |
| ISSN |
1063-6706 |
| title
|
IEEE Transactions on Fuzzy Systems |
| volume_id |
24 |
| volume |
2 (2016) |
| page_num |
260-272 |
| publisher |
| name |
Institute of Electrical and Electronics Engineers |
|
|
| keyword |
aggregation |
| keyword |
Choquet integral |
| keyword |
fuzzy measures |
| author
(primary) |
| ARLID |
cav_un_auth*0330393 |
| share |
10 |
| name1 |
Lucca |
| name2 |
G. |
| country |
ES |
|
| author
|
| ARLID |
cav_un_auth*0330394 |
| share |
10 |
| name1 |
Sanz |
| name2 |
J. A. |
| country |
ES |
|
| author
|
| ARLID |
cav_un_auth*0330395 |
| share |
10 |
| name1 |
Dimuro |
| name2 |
G. P. |
| country |
BR |
|
| author
|
| ARLID |
cav_un_auth*0298830 |
| share |
10 |
| 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 |
30 |
| name1 |
Mesiar |
| name2 |
Radko |
| institution |
UTIA-B |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0212843 |
| share |
30 |
| name1 |
Kolesárová |
| name2 |
A. |
| country |
SK |
|
| author
|
| ARLID |
cav_un_auth*0248954 |
| share |
20 |
| name1 |
Bustince |
| name2 |
H. |
| country |
ES |
| garant |
K |
|
| source |
|
| cas_special |
| abstract
(eng) |
In this paper, we introduce the notion of preaggregation function. Such a function satisfies the same boundary conditions as an aggregation function, but, instead of requiring monotonicity, only monotonicity along some fixed direction (directional monotonicity) is required.We present some examples of such functions. We propose three different methods to build preaggregation functions. We experimentally show that in fuzzy rule-based classification systems, when we use one of these methods, namely, the one based on the use of the Choquet integral replacing the product by other aggregation functions, if we consider the minimum or the Hamacher product t-norms for such construction, we improve the results obtained when applying the fuzzy reasoning methods obtained using two classical averaging operators such as the maximum and the Choquet integral. |
| RIV |
BA |
| reportyear |
2017 |
| num_of_auth |
7 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0259445 |
| confidential |
S |
| mrcbC86 |
1* Article Computer Science Artificial Intelligence|Engineering Electrical Electronic |
| mrcbT16-e |
COMPUTERSCIENCEARTIFICIALINTELLIGENCE|ENGINEERINGELECTRICALELECTRONIC |
| mrcbT16-j |
2.051 |
| mrcbT16-s |
3.408 |
| mrcbT16-4 |
Q1 |
| mrcbT16-B |
95.617 |
| mrcbT16-D |
Q1* |
| mrcbT16-E |
Q1* |
| arlyear |
2016 |
| mrcbU14 |
84963861009 SCOPUS |
| mrcbU34 |
000373948000002 WOS |
| mrcbU63 |
cav_un_epca*0253234 IEEE Transactions on Fuzzy Systems 1063-6706 1941-0034 Roč. 24 č. 2 2016 260 272 Institute of Electrical and Electronics Engineers |
|