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Titlebook: Soft Computing in Case Based Reasoning; Sankar K. Pal (Distinguished Scientist and Head),T Book 2001 Springer-Verlag London Limited 2001 a

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書目名稱Soft Computing in Case Based Reasoning
編輯Sankar K. Pal (Distinguished Scientist and Head),T
視頻videohttp://file.papertrans.cn/871/870499/870499.mp4
概述No other book covers this particular aspect of CBR; reported articles and related references are scarce so a comprehensive overview in one volume is timely.Introduces the basic concepts and theories.I
圖書封面Titlebook: Soft Computing in Case Based Reasoning;  Sankar K. Pal (Distinguished Scientist and Head),T Book 2001 Springer-Verlag London Limited 2001 a
描述.Soft Computing in Case Based Reasoning. demonstrates how various soft computing tools can be applied to design and develop methodologies and systems with case based reasoning for real-life decision-making or recognition problems..Comprising contributions from experts from all over the world, it:.- Provides an introduction to CBR and soft computing, and the relevance of their integration.- Evaluates the strengths and weaknesses of CBR in its current form.- Presents recent developments and significant applications in domains such as data-mining, medical diagnosis, knowledge-based expert systems, banking, and forensic investigation.- Addresses new information on developing intelligent systems.This book will be of particular interest to graduate students and researchers in computer science, electrical engineering and information technology but it will also be of interest to researchers and practitioners in the fields of systems design, pattern recognition and data mining.
出版日期Book 2001
關(guān)鍵詞artificial intelligence; artificial neural network; case-based reasoning; data mining; expert system; fuz
版次1
doihttps://doi.org/10.1007/978-1-4471-0687-6
isbn_ebook978-1-4471-0687-6
copyrightSpringer-Verlag London Limited 2001
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https://doi.org/10.1007/978-1-4471-0687-6artificial intelligence; artificial neural network; case-based reasoning; data mining; expert system; fuz
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Springer-Verlag London Limited 2001
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Case Based Systems: A Neuro-Fuzzy Method for Selecting Casesregions. The architecture of the network is adaptively determined through . and . of hidden nodes under supervised training. The effectiveness of the cases, thus selected by the network, is demonstrated for pattern classification problem using the 1-NN rule with the cases as the prototypes. Results are presented using real-life data.
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