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Type-I Topological Logic \(\mathbb{C}^{1}_\mathcal{T}\) and Approximate Reasoning

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3613))

Abstract

We introduce the consistent topological structure and neighborhood structure into the logical framework for providing the logical foundation and logical normalization for the approximate reasoning. We present the concept of the formulae mass, the knowledge mass and the approximating knowledge closure of the knowledge library by means of topological closure. We obtain the fundamental framework of type-I topological logics. In this framework, we present the type-I topological algorithm of the simple approximate reasoning and multi-approximate reasoning. In the frameworks of type-I strong topological logics, we present the type-I topological algorithm of multidimensional approximate reasoning and multiple multidimensional approximate reasoning. We study the type-I completeness and type-I perfection of the knowledge library in the framework of topological logical frameworks. We construct the type-I knowledge universe and prove that the second class knowledge universe of type-I is coincident with the first class knowledge universe of type-I, therefore the type-I knowledge universe is stable. We construct a self-extensive type-I knowledge library and the type-I expert system. In this expert system, the new approximate knowledge acquired by the self-extensive type-I knowledge library K I will not beyond the type-I approximate knowledge closure, (K 0)− −, of the initial knowledge library K 0. Therefore, the precision of all new acquired approximate knowledge of this automatic reasoning system will be controlled well by the type-I approximate knowledge closure (K 0)− − of the initial knowledge library K 0.

This work is supported by the project (60475001) of the National Natural Science Foundation of China.

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© 2005 Springer-Verlag Berlin Heidelberg

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Zheng, Y., Zhang, C., Yao, X. (2005). Type-I Topological Logic \(\mathbb{C}^{1}_\mathcal{T}\) and Approximate Reasoning. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_32

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  • DOI: https://doi.org/10.1007/11539506_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28312-6

  • Online ISBN: 978-3-540-31830-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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