bibtype |
J -
Journal Article
|
ARLID |
0576152 |
utime |
20240402214505.9 |
mtime |
20231005235959.9 |
SCOPUS |
85160863887 |
WOS |
000999732700002 |
DOI |
10.1007/s00500-023-08529-7 |
title
(primary) (eng) |
New horizon in fuzzy distributions: statistical distributions in continuous domains generated by Choquet integral |
specification |
page_count |
10 s. |
media_type |
P |
|
serial |
ARLID |
cav_un_epca*0258368 |
ISSN |
1432-7643 |
title
|
Soft Computing |
volume_id |
27 |
volume |
15 (2023) |
page_num |
10447-10456 |
publisher |
|
|
keyword |
fuzzy measures |
keyword |
Choquet integral |
keyword |
statistical distribution |
keyword |
Gold price |
keyword |
distorted probabilities |
keyword |
fuzzy distribution |
author
(primary) |
ARLID |
cav_un_auth*0375106 |
name1 |
Mehri-Dehnavi |
name2 |
H. |
country |
IR |
share |
40 |
garant |
K |
|
author
|
ARLID |
cav_un_auth*0261431 |
name1 |
Agahi |
name2 |
H. |
country |
IR |
share |
30 |
|
author
|
ARLID |
cav_un_auth*0101163 |
name1 |
Mesiar |
name2 |
Radko |
institution |
UTIA-B |
full_dept (cz) |
Ekonometrie |
full_dept |
Department of Econometrics |
department (cz) |
E |
department |
E |
full_dept |
Department of Econometrics |
share |
30 |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
source |
|
source |
|
cas_special |
abstract
(eng) |
In this paper, some statistical properties of the Choquet integral are discussed. As an interesting application of Choquet integral and fuzzy measures, we introduce a new class of exponential-like distributions related to monotone set functions, called Choquet exponential distributions, by combining the properties of Choquet integral with the exponential distribution. We show some famous statistical distributions such as gamma, logistic, exponential, Rayleigh and other distributions are a special class of Choquet distributions. Then, we show that this new proposed Choquet exponential distribution is better on daily gold price data analysis. Also, a real dataset of the daily number of new infected people to coronavirus in the USA in the period of 2020/02/29 to 2020/10/19 is analyzed. The method presented in this article opens a new horizon for future research. |
result_subspec |
WOS |
RIV |
BA |
FORD0 |
10000 |
FORD1 |
10100 |
FORD2 |
10101 |
reportyear |
2024 |
num_of_auth |
3 |
inst_support |
RVO:67985556 |
permalink |
https://hdl.handle.net/11104/0346457 |
confidential |
S |
mrcbC91 |
C |
mrcbT16-e |
COMPUTERSCIENCEARTIFICIALINTELLIGENCE|COMPUTERSCIENCEINTERDISCIPLINARYAPPLICATIONS |
mrcbT16-j |
0.56 |
mrcbT16-s |
0.81 |
mrcbT16-D |
Q4 |
mrcbT16-E |
Q3 |
arlyear |
2023 |
mrcbU14 |
85160863887 SCOPUS |
mrcbU24 |
PUBMED |
mrcbU34 |
000999732700002 WOS |
mrcbU63 |
cav_un_epca*0258368 Soft Computing Roč. 27 č. 15 2023 10447 10456 1432-7643 1433-7479 Springer |
|