Abstract
The study is concerned with the fundamentals of granular computing. Granular computing, as the name itself stipulates, deals with representing information in the form of some aggregates (embracing a number of individual entitites) and their processing. We elaborate on the rationale behind granular computing. Next, a number offormal frameworks of information granulation are discussed including several alternatives such as fuzzy sets, interval analysis, rough sets, and probability. The notion of granularity itself is defined and quantified. A design agenda of granular computing is formulated and the key design problems are raised. A number of granular architectures are also discussed with an objective of dealinating the fundamental algorithmic and conceptual challenges.It is shown that the use of information granules of different size (granularity) lends itself to general pyramid architectures of information processing. The role of encoding and decoding mechanisms visible in this setting is also discussed in detail along with some particular solutions. The intent of this paper is to elaborate on the fundamentals and put the entire area in a certain perspective while not moving into specific algorithmic details.
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Pedrycz, W. (2000). Granular Computing : An Introduction. In: Kasabov, N. (eds) Future Directions for Intelligent Systems and Information Sciences. Studies in Fuzziness and Soft Computing, vol 45. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1856-7_15
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DOI: https://doi.org/10.1007/978-3-7908-1856-7_15
Publisher Name: Physica, Heidelberg
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Online ISBN: 978-3-7908-1856-7
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