Results 11 to 20 of about 8,185,214 (318)

Multigranulation fuzzy rough set over two universes and its application to decision making

Knowledge-Based Systems, 2017
B. Sun, Weimin Ma, Y. Qian
semanticscholar   +3 more sources

Attribute Reduction of Variable Precision Fuzzy Rough Set Based on Misclassification Cost [PDF]

Jisuanji kexue, 2022
Attribute reduction is a hot research issue in rough set.In this paper, how to reduce redundant attributes without increasing the misclassification cost is studied.Firstly, the minimum misclassification degree of variable precision fuzzy rough sets is ...
WANG Zi-yin, LI Lei-jun, MI Ju-sheng, LI Mei-zheng, XIE Bin
doaj   +1 more source

Fuzzy-rough set models and fuzzy-rough data reduction

Croatian Operational Research Review, 2020
Rough set theory is a powerful tool to analysis the information systems. Fuzzy rough set is introduced as a fuzzy generalization of rough sets. This paper reviewed the most important contributions to the rough set theory, fuzzy rough set theory and their
Hassan Mishmast Nehi, Alireza Mansouri Ghroutkhar   +1 more
doaj   +1 more source

Empirical analysis of rough set categorical clustering techniques based on rough purity and value set [PDF]

, 2017
Clustering a set of objects into homogeneous groups is a fundamental operation in data mining. Recently, attention has been put on categorical data clustering, where data objects are made up of non-numerical attributes.
Abdulhasan, Raed abdulkareem, Ahmed, Mustafa S., Al-Jawhar, Yasir Amer, Alwan, Mohammed H., Farhood, Hussein M., Ramli, Khairun N.   +5 more
core   +1 more source

Autonomous clustering using rough set theory [PDF]

, 2008
This paper proposes a clustering technique that minimises the need for subjective human intervention and is based on elements of rough set theory. The proposed algorithm is unified in its approach to clustering and makes use of both local and global ...
A. K. Jain, A. K. Jain, A. Skowron, B. J. F. Manly, B. S. Everitt, C. L. Bean, C. L. Bean, Chandra Kambhampati, Charlotte Bean, D. Dubois, E. W. Forgey, F. H. C. Marriott, F. Höppner, G. H. Ball, J. A. Hartigan, J. B. MacQueen, J. C. Bezdek, J. C. Dunn, J. H. Ward, J. Komorowski, J. S. R. Jang, M. R. Anderberg, M. S. Aldenderfer, M. S. Kamel, P. Sneath, R. C. Jancey, R. R. Sokal, R. R. Yegar, S. Sharma, S. Z. Selim, T. Okuzaki, T. Sorensen, Z. Pawlak, Z. Pawlak   +33 more
core   +1 more source

An efficient feature selection based Bayesian and Rough set approach for intrusion detection

Applied Soft Computing, 2020
The exponential growth of network size leads to increase attacks and intrusions. Detection of these attacks from the network has turned into a noteworthy issue of security. An intrusion detection system is an important approach to achieves high detection
Mahendra Prasad, S. Tripathi, K. Dahal
semanticscholar   +1 more source

Fermatean neutrosophic rough set [PDF]

Computational Algorithms and Numerical Dimensions
In order to balance uncertainty, a reasonable approximation of a crisp set that yields lower as well as upper approximations of the set is made. Here, first, a special class of Fermatean Neutrosophic Set is devised by associating the Neutrosophic Set ...
S Bhuvaneshwari, C Antony Crispin Sweety, R Sumathi   +2 more
doaj   +1 more source

New neighborhood based rough sets [PDF]

, 2015
Neighborhood based rough sets are important generalizations of the classical rough sets of Pawlak, as neighborhood operators generalize equivalence classes.
I Couso, JA Pomykala, M Restrepo, M Restrepo, T Yang, W Zhu, W Zhu, W Żakowski, YY Yao, YY Yao, Z Bonikowski, Z Pawlak   +11 more
core   +1 more source

The Upper and Lower Approximations in Rough Subgroupoid of a Groupoid

Moroccan Journal of Pure and Applied Analysis, 2018
In this article, we introduce the concept of rough subgroupoid of a groupoid as a generalization of a rough subgroup and give some features about the lower and the upper approximations in a groupoid [1]. We give some of the characterization of them.
Tasbozan H., Icen I.
doaj   +1 more source

The use of rough rules in the selection of topographic objects for generalizing geographical information

Polish Cartographical Review, 2020
Selection is a key element of the cartographic generalisation process, often being its first stage. On the other hand it is a component of other generalisation operators, such as simplification.
Fiedukowicz Anna
doaj   +1 more source