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Titlebook: Data Mining and Knowledge Management; Chinese Academy of S Yong Shi,Weixuan Xu,Zhengxin Chen Conference proceedings 2004 Springer-Verlag Be

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Data Mining and Knowledge Management978-3-540-30537-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Atomic Super-Resolution Tomographyign for single factor cDNA two-color microarray experiments. Relative efficiencies of proposed designs in Yang ([13]) are studied within the framework of incomplete block designs as well as row-column designs. Such efficiencies are investigated under fixed and mixed analysis of variance models. Furthermore, a real data analysis is conducted.
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Sheaves and projective toric varietiesal databases. It is shown how the tool can support the process of exploration of data properties and selecting a small number of preferable items from the database by application a graphic form of goal programming. The graphic Web application server is considered which implements the data mining too
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https://doi.org/10.1007/978-1-4612-4664-0n and transactions. Nevertheless, without continuous expanding and upgrading our habitual domains (HD) and competence set (CS), KM may lead us to decision traps and making wrong decisions. This article introduces the concepts of habitual domains and competence set analysis in such a way that we coul
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Twisted Chain Complexes and Twisted Homologyte independently, the interaction among the influences from the feature attributes toward the classifying attribute is described by a signed fuzzy measure. An optimized Choquet integral with respect to an optimized signed fuzzy measure is adopted as a nonlinear projector to map each observation from
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Complexes in Cofibration Categoriesferent degrees instead of a definite class by crisp classification. This paper studies the usage of fuzzy strategy in classification. Two fuzzy algorithms for sequential self-organizing map and learning vector quantization are proposed based on fuzzy projection and learning rules. The derived classi
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The Automorphism Extension Property,ate values of the components are constructed, and each value in the group has its trail information. In each iteration of the ant colony algorithm, the method first chooses initial values of the components using the trail information. Then, crossover and mutation can determine the values of the comp
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