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Interpretation of Extended Pawlak Flow Graphs Using Granular Computing

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Book cover Transactions on Rough Sets VIII

Part of the book series: Lecture Notes in Computer Science ((TRS,volume 5084))

Abstract

In this paper, we mainly discuss the relationship between the extended Pawlak flow graph (EFG) with granular computing (GrC), and develop a both simple and concrete model for EFG using GrC. The distinct advantage is that we can resort to merits of GrC to benefit us in analyzing and processing data using flow graph, for its structure is inherently consistent with GrC, which provides us with both structured thinking at the philosophical level and structured problem solving at the practical level. In pursuit of our purpose, at first, EFG will be mainly discussed in three aspects under GrC, namely, granulation of EFG, some relationships and operations of granules. Under the framework of GrC model, inference and reformation in EFG can be easily implemented in virtue of decomposition and composition of granules, respectively. Based on this scheme, two efficient reduction algorithms about EFG are also proposed.

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Authors and Affiliations

  1. College of Computer Science, Jilin University, Changchun, 130012, China

    Huawen Liu, Jigui Sun & Huijie Zhang

  2. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,  , Changchun, 130012, China

    Huawen Liu & Jigui Sun

  3. College of Computer, Northeast Normal University, Changchun, 130021, China

    Huijie Zhang

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  1. Huawen Liu
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  2. Jigui Sun
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  3. Huijie Zhang
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James F. Peters Andrzej Skowron

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Liu, H., Sun, J., Zhang, H. (2008). Interpretation of Extended Pawlak Flow Graphs Using Granular Computing. In: Peters, J.F., Skowron, A. (eds) Transactions on Rough Sets VIII. Lecture Notes in Computer Science, vol 5084. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85064-9_6

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  • DOI: https://doi.org/10.1007/978-3-540-85064-9_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85063-2

  • Online ISBN: 978-3-540-85064-9

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