A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses
In medical science, disease diagnosis is one of the difficult tasks for medical experts who are confronted with challenges in dealing with a lot of uncertain medical information. And different medical experts might express their own thought about the medical knowledge base which slightly differs fro...
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2015-01-01
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Series: | Computational and Mathematical Methods in Medicine |
Online Access: | http://dx.doi.org/10.1155/2015/292710 |
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doaj-ec158f7bcb454f339deeaad683d1b2432020-11-24T21:20:17ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182015-01-01201510.1155/2015/292710292710A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical DiagnosesChao Zhang0Deyu Li1Yan Yan2School of Computer and Information Technology, Shanxi University, Taiyuan, Shanxi 030006, ChinaSchool of Computer and Information Technology, Shanxi University, Taiyuan, Shanxi 030006, ChinaSchool and Hospital of Stomatology, Peking University, Beijing 100089, ChinaIn medical science, disease diagnosis is one of the difficult tasks for medical experts who are confronted with challenges in dealing with a lot of uncertain medical information. And different medical experts might express their own thought about the medical knowledge base which slightly differs from other medical experts. Thus, to solve the problems of uncertain data analysis and group decision making in disease diagnoses, we propose a new rough set model called dual hesitant fuzzy multigranulation rough set over two universes by combining the dual hesitant fuzzy set and multigranulation rough set theories. In the framework of our study, both the definition and some basic properties of the proposed model are presented. Finally, we give a general approach which is applied to a decision making problem in disease diagnoses, and the effectiveness of the approach is demonstrated by a numerical example.http://dx.doi.org/10.1155/2015/292710 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chao Zhang Deyu Li Yan Yan |
spellingShingle |
Chao Zhang Deyu Li Yan Yan A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses Computational and Mathematical Methods in Medicine |
author_facet |
Chao Zhang Deyu Li Yan Yan |
author_sort |
Chao Zhang |
title |
A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses |
title_short |
A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses |
title_full |
A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses |
title_fullStr |
A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses |
title_full_unstemmed |
A Dual Hesitant Fuzzy Multigranulation Rough Set over Two-Universe Model for Medical Diagnoses |
title_sort |
dual hesitant fuzzy multigranulation rough set over two-universe model for medical diagnoses |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2015-01-01 |
description |
In medical science, disease diagnosis is one of the difficult tasks for medical experts who are confronted with challenges in dealing with a lot of uncertain medical information. And different medical experts might express their own thought about the medical knowledge base which slightly differs from other medical experts. Thus, to solve the problems of uncertain data analysis and group decision making in disease diagnoses, we propose a new rough set model called dual hesitant fuzzy multigranulation rough set over two universes by combining the dual hesitant fuzzy set and multigranulation rough set theories. In the framework of our study, both the definition and some basic properties of the proposed model are presented. Finally, we give a general approach which is applied to a decision making problem in disease diagnoses, and the effectiveness of the approach is demonstrated by a numerical example. |
url |
http://dx.doi.org/10.1155/2015/292710 |
work_keys_str_mv |
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1726003101112991744 |