Results 41 to 50 of about 39,193 (212)

Rough set-based entropy measure with weighted density outlier detection method

Open Computer Science, 2022
The rough set theory is a powerful numerical model used to handle the impreciseness and ambiguity of data. Many existing multigranulation rough set models were derived from the multigranulation decision-theoretic rough set framework. The multigranulation
Sangeetha Tamilarasu, Geetha Mary Amalanathan   +1 more
doaj   +1 more source

Autonomous clustering using rough set theory [PDF]

International Journal of Automation and Computing, 2008
This paper proposes a clustering technique that minimises the need for subjective\ud human intervention and is based on elements of rough set theory. The proposed algorithm is\ud unified in its approach to clustering and makes use of both local and global data properties to\ud obtain clustering solutions. It handles single-type and mixed attribute data
Kambhampati, Chandra, Bean, Charlotte
openaire   +2 more sources

A Generalized Multigranulation Rough Set Model by Synthesizing Optimistic and Pessimistic Attitude Preferences

Mathematics
Attitude preference plays an important role in multigranulation data mining and decision-making. That is, different attitude preferences lead to different results.
Hongwei Wang, Huilai Zhi, Yinan Li, Daxin Zhu, Jianbing Xiahou   +4 more
doaj   +1 more source

Granular Space Reduction to a β Multigranulation Fuzzy Rough Set

Abstract and Applied Analysis, 2014
Multigranulation rough set is an extension of classical rough set, and optimistic multigranulation and pessimistic multigranulation are two special cases of it. β multigranulation rough set is a more generalized multigranulation rough set. In this paper,
Junyi Zhou, Shaohui Ma, Jianzhen Li
doaj   +1 more source

New Uncertainty Measure of Rough Fuzzy Sets and Entropy Weight Method for Fuzzy-Target Decision-Making Tables

Journal of Applied Mathematics, 2014
In the rough fuzzy set theory, the rough degree is used to characterize the uncertainty of a fuzzy set, and the rough entropy of a knowledge is used to depict the roughness of a rough classification.
Huani Qin, Darong Luo
doaj   +1 more source

Some Inequalities Combining Rough and Random Information

Entropy, 2018
Rough random theory, generally applied to statistics, decision-making, and so on, is an extension of rough set theory and probability theory, in which a rough random variable is described as a random variable taking “rough variable” values.
Yujie Gu, Qianyu Zhang, Liying Yu
doaj   +1 more source

Soft covering based rough graphs and corresponding decision making

Open Mathematics, 2019
Soft set theory and rough set theory are two new tools to discuss uncertainty. Graph theory is a nice way to depict certain information. Particularly soft graphs serve the purpose beautifully.
Park Choonkil, Shah Nasir, Rehman Noor, Ali Abbas, Ali Muhammad Irfan, Shabir Muhammad   +5 more
doaj   +1 more source

Approximation of Rough Soft Set and Its Application to Lattice

Fuzzy Information and Engineering, 2015
The approximation of soft set is presented in modified soft rough (MSR) approximation space in this paper, i.e., approximation of an information system with respect to another information one.
Sankar Kumar Roy, Susanta Bera
doaj   +1 more source

An Optimal Hierarchical Approach for Oral Cancer Diagnosis Using Rough Set Theory and an Amended Version of the Competitive Search Algorithm. [PDF]

Diagnostics (Basel), 2023
Song S, Ren X, He J, Gao M, Wang J, Wang B.   +5 more
europepmc   +1 more source

Covering-Based Rough Sets on Eulerian Matroids

Journal of Applied Mathematics, 2013
Rough set theory is an efficient and essential tool for dealing with vagueness and granularity in information systems. Covering-based rough set theory is proposed as a significant generalization of classical rough sets.
Bin Yang, Ziqiong Lin, William Zhu
doaj   +1 more source