A dual hesitant fuzzy multigranulation rough set over two-universe model for medical diagnoses

27Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

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.

Cite

CITATION STYLE

APA

Zhang, C., Li, D., & Yan, Y. (2015). A dual hesitant fuzzy multigranulation rough set over two-universe model for medical diagnoses. Computational and Mathematical Methods in Medicine, 2015. https://doi.org/10.1155/2015/292710

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free