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Titlebook: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing; 9th International Co Guoyin Wang,Qing Liu,Andrzej Skowron Conference proceedin

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Extracting Structure of Medical Diagnosis: Rough Set Approach It is because rule induction methods induce probabilistic rules that discriminates between a target concept and other concepts, assuming that all the concepts are on the same level. However, medical experts assume that all the concepts of diseases are belonging to the different level of hierarchy.
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A Kind of Linearization Method in Fuzzy Control System Modeling method can turn a nonlinear model with variable coefficients into a linear model with variable coefficients in the way that the membership functions of the fuzzy sets in fuzzy partitions of the universes are changed from triangle waves into rectangle waves. However, the linearization models are inc
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A Common Framework for Rough Sets, Databases, and Bayesian Networksrst order modal logic (FOML) to formulate a common framework for rough sets, databases, and Bayesian networks. The relational view of the semantics of first order modal logic provides a unified interpretation of many related concepts.
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A New Rough Sets Model Based on Database Systemsm based on the database theory to take advantage of the very efficient set-oriented database operation. We present a new set of algorithms to calculate core, reduct based on our new database based rough set model. Almost all the operations used in generating core, reduct in our model can be performe
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A Rough Set and Rule Tree Based Incremental Knowledge Acquisition Algorithmo find an algorithm that can learn new knowledge quickly based on original knowledge learned before and the knowledge it acquires is efficient in real use. In this paper, we develop a rough set and rule tree based incremental knowledge acquisition algorithm. It can learn from a domain data set incre
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