Results 211 to 220 of about 10,010,302 (244)

A discretization method for rough sets theory

Intelligent Data Analysis, 2001
The Rough Sets Theory, as a powerful knowledge-mining tool, has been widely applied to acquire knowledge in the medical, engineering and financial domains. However, this powerful tool cannot be applied to real-world classification tasks involving continuous features. This requires the utilization of discretization methods.
Shen, L., Tay, F.E.H.
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Rough Approximate Operators: Axiomatic Rough Set Theory

1994
In rough set theory, the upper and lower approximations are defined in terms of equivalence relation. In this paper, the reverse problem is considered. Let H and L are two abstract operators acting on the power set of U, the universe of discourse. If the two operators satisfy six axioms, then there is an equivalence relation defined on U such that H(X)
Tsau Young Lin, Qing Liu 0011
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Combination of evidence in rough set theory

Proceedings of ICCI'93: 5th International Conference on Computing and Information, 2002
Studies the knowledge refinement resulting from the accumulation of evidence in rough set theory. Some of the important and practical issues, such as the use of different sample spaces, are discussed. This new concept of evidence accumulation broadens the framework of rough sets for the further development of intelligent information systems. >
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Rough Set Theory in Conflict Analysis

2001
The importance of multi-agents systems, models of agents’ interaction is increasing nowadays as distributed systems of computers started to play a significant role in society. An interaction occurs when two or more agents, which have to act in order to attain their objectives, are brought into a dynamic relationship.
Rafal Deja, Dominik Slezak
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Rough Set Theory of Shape Perception

2007
Humans can easily recognize complex objects even if values of their attributes are imprecise and often inconsistent. It is not clear how the brain processes uncertain visual information. We have tested electrophysiological activity of the visual cortex (area V4), which is responsible for shape classifications.
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Rough Set Theory.

Künstliche Intell., 2001
pages 1 ...
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Fuzzy Extension of Rough Sets Theory

1998
In this paper we consider many approximation spaces for rough theories, all of which are concrete realizations of an abstract structure stronger than the one introduced in [2] and defined in the following way: $$ \mathfrak{A}: = \langle \Sigma ,\mathcal{D}(\Sigma ), \leqslant ,0,1\rangle $$ where: 1. 〈Σ, ∧.
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Rough Set Theory on Topological Spaces

2014
We consider that Rough Sets that arise in an Information System from the point of view of Topology. The main purpose of this paper is to show how well known topological concepts are closely related to Rough Sets and generalize the Rough sets in the frame work of Topological Spaces. We presented the properties of Quasi-Discrete topology and Π0-Roughsets.
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Granular Computing and Rough Set Theory

2007
Granulation plays an essential role in human cognition and has a position of centrality in both granular computing and rough set theory. Informally, granulation involves partitioning of an object into granules, with a granule being a clump of elements drawn together by indistinguishability, equivalence, similarity, proximity or functionality.
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Distance: A more comprehensible perspective for measures in rough set theory

Knowledge-Based Systems, 2012
Jiye Liang, Yuhua Qian, Ru Li
exaly