Results 271 to 280 of about 1,803,229 (305)

A hypergraph model of granular computing

2008 IEEE International Conference on Granular Computing, 2008
A hypergraph model of granular computing is proposed. In this model, a vertex refers to an object, a hyperedge corresponds to a granule, a hypergraph relates to a set of granules and their relations in a specific granularity, and a series of hypergraphs correspond to a hierarchical structure.
Guang Chen, Ning Zhong 0001, Yiyu Yao
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Granular computing with shadowed sets

International Journal of Intelligent Systems, 2002
Summary: The theory of shadowed sets is one among several key contributors to the area of granular computing. As the name stipulates, granular computing embraces processing of information granules. By information granules we mean collections of entities being assembled together in order to achieve a certain conceptual and/or computational feasibility ...
Witold Pedrycz, George Vukovich
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Granular Computing

2009
It is well accepted that in many real life situations information is not certain and precise but rather uncertain or imprecise. To describe uncertainty probability theory emerged in the 17th and 18th century. Bernoulli, Laplace and Pascal are considered to be the fathers of probability theory.
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Theoretical Study of Granular Computing

2006
We propose a higher order logic called as the granular logic. This logic is introduced as a tool for investigating properties of granular computing. In particular, constants of this logic are of the form m(F), where F is a formula (e.g., Boolean combination of descriptors) in a given information system.
Qing Liu 0011, Hui Sun
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Covering-based granular computing

2008 IEEE International Conference on Granular Computing, 2008
Granular computing is a methodology for intelligent information processing. It uses granules such as classes, clusters, subsets, and blocks to construct an efficient computational model for complex applications with huge amounts of data, information and knowledge. This subject is related to other fields such as artificial intelligence, cluster analysis,
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Intensional theory of granular computing

Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Granular computing for data mining

SPIE Proceedings, 2006
Granular computing, as an emerging research field, provides a conceptual framework for studying many issues in data mining. This paper examines some of those issues, including data and knowledge representation and processing. It is demonstrated that one of the fundamental tasks of data mining is searching for the right level of granularity in data and ...
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A Categorial Basis for Granular Computing

2007
The theory of granular computing is accorded a formal mathematical basis, by presenting its main features using a category-theoretic language. A category $\cal C_G$ of granulations is proposed. It is shown how two main operations between granulations, viz. coarsening and refinement, can be expressed in terms of $\cal C_G$-morphisms.
Mohua Banerjee, Yiyu Yao
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Granular Computing

2003
Andrzej Bargieła, Pedrycz, Witold
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Concept Granular Computing Systems

2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009
Object-oriented and property-oriented concept lattices are constructed based on rough set theory. In this paper, a uniform mathematical model-concept granular computing system is first established by mappings on two complete lattices. In this framework, object-oriented and property-oriented concept granular computing systems are introduced for property-
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