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Titlebook: Knowledge-Based Neurocomputing: A Fuzzy Logic Approach; Eyal Kolman,Michael Margaliot Book 2009 Springer-Verlag Berlin Heidelberg 2009 All

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發(fā)表于 2025-3-21 17:25:39 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Knowledge-Based Neurocomputing: A Fuzzy Logic Approach
編輯Eyal Kolman,Michael Margaliot
視頻videohttp://file.papertrans.cn/545/544218/544218.mp4
概述Presents the state of the art in knowledge-based neurocomputing.Presents a new connection between artificial neural networks (ANNs) and a special fuzzy rule-base - the all permutations fuzzy rule-base
叢書名稱Studies in Fuzziness and Soft Computing
圖書封面Titlebook: Knowledge-Based Neurocomputing: A Fuzzy Logic Approach;  Eyal Kolman,Michael Margaliot Book 2009 Springer-Verlag Berlin Heidelberg 2009 All
描述.In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the .Fuzzy All-permutations Rule-Base (FARB).. They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB. ..The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for .knowledge-based neurocomputing. in artificial neural networks..
出版日期Book 2009
關(guān)鍵詞All-Permutations Fuzzy Rule Base; Equivalence; Fuzzy; Fuzzy Rule-Based Systems; Knowedge Refinement; Know
版次1
doihttps://doi.org/10.1007/978-3-540-88077-6
isbn_softcover978-3-642-09985-4
isbn_ebook978-3-540-88077-6Series ISSN 1434-9922 Series E-ISSN 1860-0808
issn_series 1434-9922
copyrightSpringer-Verlag Berlin Heidelberg 2009
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沙發(fā)
發(fā)表于 2025-3-22 00:11:30 | 只看該作者
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978-3-642-09985-4Springer-Verlag Berlin Heidelberg 2009
地板
發(fā)表于 2025-3-22 07:17:24 | 只看該作者
5#
發(fā)表于 2025-3-22 09:23:57 | 只看該作者
,The FARB–ANN Equivalence,t of a specific type of ANN. This provides a . representation of the ANN functioning. As a corollary, we obtain results that can be used for KE from, and KBD of, ANNs. Simple examples are used to demonstrate the main ideas. The remainder of this work is devoted to extending this approach to larger-scale networks.
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發(fā)表于 2025-3-22 15:40:10 | 只看該作者
Knowledge Extraction Using the FARB,rameters are determined by the network structure and parameters. This transforms the knowledge embedded in the network into a set of symbolic rules stated using natural language. If necessary, the FARB can be further simplified to increase its comprehensibility.
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https://doi.org/10.1007/978-3-540-88077-6All-Permutations Fuzzy Rule Base; Equivalence; Fuzzy; Fuzzy Rule-Based Systems; Knowedge Refinement; Know
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