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Titlebook: Developments in Soft Computing; Robert John,Ralph Birkenhead Conference proceedings 2001 Springer-Verlag Berlin Heidelberg 2001 Artificial

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書目名稱Developments in Soft Computing
編輯Robert John,Ralph Birkenhead
視頻videohttp://file.papertrans.cn/271/270282/270282.mp4
概述Includes supplementary material:
叢書名稱Advances in Intelligent and Soft Computing
圖書封面Titlebook: Developments in Soft Computing;  Robert John,Ralph Birkenhead Conference proceedings 2001 Springer-Verlag Berlin Heidelberg 2001 Artificial
描述Soft Computing has come of age. In particular, Artificial Neural Networks, Fuzzy Logic and Evolutionary Computing now play an important role in many domains where traditional techniques have been found wanting. As this volume confirms, hybrid solutions that combine more than one of the Soft Computing approaches are particularly successful in many problem areas. This volume contains papers presented at the International Conference on Recent Advances in Soft Computing 2000 at De Montfort University in Leicester. The contributions cover both theoretical developments and practical applications in the various areas of Soft Computing.
出版日期Conference proceedings 2001
關(guān)鍵詞Artificial Neural Networks; Evolutionary Computing; Fuzzy; Fuzzy Logic; Fuzzy-Logik; artificial neural ne
版次1
doihttps://doi.org/10.1007/978-3-7908-1829-1
isbn_softcover978-3-7908-1361-6
isbn_ebook978-3-7908-1829-1Series ISSN 1867-5662 Series E-ISSN 1867-5670
issn_series 1867-5662
copyrightSpringer-Verlag Berlin Heidelberg 2001
The information of publication is updating

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Resemblance Relations and Fuzzy Weak Orderingsesemblance Relation on the fuzzy power set [0, 1]. by means of the Duality Principle for Fuzzy Sets [Ovchinnikov, 94]. In this way, Resemblance Relations can be seen as a generalization of Fuzzy Weak Orders.
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Roughness Indicator Fuzzy Set. The relationships between the different types of indices of fuzziness and the roughness measures are established. It is also observed that nearest ordinary sets play important roles in this case. Consequently, the concept of Roughness Indicator Fuzzy class is also proposed.
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Fuzzy Symptoms and a Decision Support Index for the Early Diagnosis of Confusable Diseasesnty of duration. We begin by briefly considering the context of use of the process and then go on to formally describe the fuzzy approach and the algorithm that produces the improved index. Finally, we show how the improved index values relate to two confusable diseases given a range of symptom strengths.
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https://doi.org/10.1007/978-3-642-24458-2esemblance Relation on the fuzzy power set [0, 1]. by means of the Duality Principle for Fuzzy Sets [Ovchinnikov, 94]. In this way, Resemblance Relations can be seen as a generalization of Fuzzy Weak Orders.
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