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Author: search.filters.author.Chitcharoen, DoungratSubject: search.filters.subject.Flow graphs

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    An extension of rough set approximation to flow graph based data analysis
    (2010-12-01)
    Chitcharoen, Doungrat
    ;
    Pattaraintakorn, Puntip
    This paper concerns some aspects of mathematical flow graph based data analysis. In particular, taking a flow graph view on rough sets' categories and measures leads to a new methodology of inductively reasoning form data. This perspective shows interesting relationships and properties among rough set, flow graphs and inverse flow graphs. A possible car dealer application is outlined and discussed. Evidently, our new categories and measures assist and alleviate some limitations in flow graphs to discover new patterns and explanations. © 2010 Springer-Verlag Berlin Heidelberg.
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    Novel matrix forms of rough set flow graphs with applications to data integration
    (2010-11-01)
    Chitcharoen, Doungrat
    ;
    Pattaraintakorn, Puntip
    Pawlak's flow graphs have attracted both practical and theoretical researchers because of their ability to visualize information flow. In this paper, we invent a new schema to represent throughflow of a flow graph and three coefficients of both normalized and combined normalized flow graphs in matrix form. Alternatively, starting from a flow graph with its throughflow matrix, we reform Pawlak's formulas to calculate these three coefficients in flow graphs by using matrix properties. While traditional algorithms for computing these three coefficients of the connection are exponential in l, an algorithm using our matrix representation is polynomial in l, where l is the number of layers of a flow graph. The matrix form can simplify computation, improve time complexity, alleviate problems due to missing coefficients and hence help to widen the applications of flow graphs. Practically, data sets often reside at different sources (heterogeneous data sources). Their individual analysis at each source is inadequate and requires special treatment. Hence, we introduce a composition method for flow graphs and corresponding formulas for calculating their coefficients which can omit some data sharing. We provide a real-world experiment on the Promotion of Academic Olympiads and Development of Science Education Foundation (POSN) data set which illustrates a desirable outcome and the advantages of the proposed matrix forms and the composition method. © 2010 Elsevier Ltd. All rights reserved.
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    Towards theories of fuzzy set and rough set to flow graphs
    (2008-01-01)
    Chitcharoen, Doungrat
    ;
    Pattaraintakorn, Puntip
    Mathematical rough set theory and fuzzy set theory have attracted both practical and theoretical researchers from their efficiently and effectively to analyze real-world data. A novel and significant extension is called flow graphs. In this paper, we Introduced how to calculate certainty, coverage and strength coefficients of decision rules from fuzzy attributes in a flow graph. Furthermore, we relax concept of mutual exclusion and introduced four new propositions of certainty and coverage coefficients for decision rules extracted from flow graph. An example calculation of these coefficients is provided. We also demonstrate real-world experiment on POSN data set. Several case studies illustrate a desirable outcome. © 2008 IEEE.