Results 251 to 260 of about 67,600 (304)

Information granule decomposition.

Fundam. Informaticae, 2001
Summary: Information sources provide us with granules of information that must be transformed, analyzed and built into structures that support problem solving. One of the main goals of information granule calculi is to develop algorithmic methods for construction of complex information granules from elementary ones by means of available operations and ...
Andrzej Skowron, Jaroslaw Stepaniuk
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Rough Sets and Information Granulation

2003
In this paper, the study of the evolution of approximation space theory and its applications is considered in the context of rough sets introduced by Zdzislaw Pawlak and information granulation as well as computing with words formulated by Lotfi Zadeh. Central to this evolution is the rough-mereological approach to approximation of information granules.
James F. Peters, Andrzej Skowron, Piotr Synak, Sheela Ramanna   +3 more
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Construction of Information Granules: From Data and Perceptions to Information Granules

2008
We focus on the development of fuzzy sets by presenting various ways of designing fuzzy sets and determining their membership functions.
Bruno Apolloni, Witold Pedrycz, Simone Bassis, Dario Malchiodi   +3 more
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Information Granules for Spatial Reasoning

2000
The authors consider schemes of approximate reasoning approaches to transforming of information granules from different information sources. By tuning the parameters of schemes, the information granules representing patterns relevant to given tasks can be generated.
Andrzej Skowron, Jaroslaw Stepaniuk, Shusaku Tsumoto   +2 more
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The information granulation in discretization

Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693), 2004
Discretization is a vehicle of abstraction that supports a conversion of clouds of numeric data into more tangible information granules, which can be represented as hyper-boxes in R". A partial ordering of all discretization schemes for a given information table is defined to describe the relative granularity. All discretized tables form a hierarchical
null Li-Hong Wang, null Shu-Cui Zhang, null Hui Fan, null Geng-Feng Wu   +3 more
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Tolerance Information Granules

2006
In this paper we discuss tolerance information granule systems. We present examples of information granules and we consider two kinds of basic relations between them, namely inclusion and closeness. The relations between more complex information granules can be defined by extension of the relations defined on parts of information granules.
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Representation of Uncertainty with Information and Probabilistic Information Granules

International Journal of Fuzzy Systems, 2016
Linguistic representations by human brain are often characterized with an intertwined combination of imprecision (due to incomplete knowledge), vagueness, or uncertainty. A powerful framework of information and probabilistic information granules is proposed to model this combination of different facets of uncertainty in natural representations without ...
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Description Languages for Relational Information Granules

Fundamenta Informaticae, 2015
Information granulation is a powerful tool for data analysis and processing. However, not much attention has been devoted to application of this tool to data stored in a relational structure. This paper extends the notion of information granules to a relational case. Two information systems intended to store relational data are proposed.
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Recursive Information Granulation

2003
This chapter elaborates on the conceptual and algorithmic framework of information granulation. We provide a detailed algorithm of information granulation that is cast as an optimization problem reconciling two conflicting design criteria namely a specificity of information granules and their experimental relevance (coverage of numeric data).
Andrzej Bargiela, Witold Pedrycz
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Information granules in medical differential diagnosis

2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2012
This paper discusses a correspondence between the core ideas of rough sets and medical differential diagnosis. Classically, a disease is defined as a set of symptoms, each of which gives the degree of confidence and coverage for the diagnosis.
Shusaku Tsumoto, Shoji Hirano
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