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  • 1
    UID:
    almahu_BV019318074
    Format: XX, 853 S. : Ill., graph. Darst.
    ISBN: 3-540-22117-4
    Series Statement: Lecture notes in computer science 3066 : Lecture notes in artificial intelligence
    Language: English
    Keywords: Grobmenge ; Soft Computing ; Data Mining ; Granular Computing ; Mustererkennung ; Konferenzschrift ; Konferenzschrift ; Konferenzschrift
    URL: Cover
    Author information: Tsumoto, Shusaku, 1963-
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    kobvindex_ZLB13754201
    Format: XX, 853 Seiten , graph. Darst. , 24 cm
    ISBN: 3540221174
    Series Statement: Lecture notes in computer science
    Note: Literaturangaben , Text engl.
    Language: English
    Keywords: Grobmenge ; Kongress ; Uppsala 〈2004〉 ; Soft Computing ; Kongress ; Uppsala 〈2004〉 ; Data Mining ; Kongress ; Uppsala 〈2004〉 ; Granular Computing ; Kongress ; Uppsala 〈2004〉 ; Mustererkennung ; Kongress ; Uppsala 〈2004〉 ; Kongress ; Konferenzschrift
    Author information: Tsumoto, Shusaku
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  • 3
    UID:
    gbv_749105356
    Format: Online-Ressource (XX, 853 p. Also available online) , digital
    Edition: Springer eBook Collection. Computer Science
    ISBN: 9783540259299 , 3540221174 , 9783540221173
    Series Statement: Lecture Notes in Computer Science 3066
    Content: This book constitutes the refereed proceedings of the 4th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2004, held in Uppsala, Sweden in June 2004. The 45 revised full papers and 60 revised short papers presented together with 3 invited papers and a bibliographic project report were carefully reviewed and selected from 248 submissions. The papers are organized in topical sections on theory, logic and rough sets, granular computing, rough and fuzzy relations, foundations of data mining, incomplete information systems, interestingness, multiagents and information systems, fuzzy logic and modeling, rough classification, rough sets and probabilities, variable precision rough sets models, spatial reasoning, reduction, rule induction, rough sets and neural networks, clustering, data mining, image and signal recognition, information retrieval, decision support, adaptaive and optimization methods, bioinformatics, and medical applications
    Note: Literaturangaben
    Additional Edition: ISBN 9783540221173
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783662187296
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783540221173
    Language: English
    URL: Volltext  (lizenzpflichtig)
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  • 4
    UID:
    almahu_9947920573902882
    Format: XX, 860 p. , online resource.
    ISBN: 9783540259299
    Series Statement: Lecture Notes in Computer Science, 3066
    Content: In recent years rough set theory has attracted the attention of many researchers and practitioners all over the world, who have contributed essentially to its development and applications. Weareobservingagrowingresearchinterestinthefoundationsofroughsets, including the various logical, mathematical and philosophical aspects of rough sets. Some relationships have already been established between rough sets and other approaches, and also with a wide range of hybrid systems. As a result, rough sets are linked with decision system modeling and analysis of complex systems, fuzzy sets, neural networks, evolutionary computing, data mining and knowledge discovery, pattern recognition, machine learning, and approximate reasoning. In particular, rough sets are used in probabilistic reasoning, granular computing (including information granule calculi based on rough mereology), intelligent control, intelligent agent modeling, identi?cation of autonomous s- tems, and process speci?cation. Methods based on rough set theory alone or in combination with other - proacheshavebeendiscoveredwith awide rangeofapplicationsinsuchareasas: acoustics, bioinformatics, business and ?nance, chemistry, computer engineering (e.g., data compression, digital image processing, digital signal processing, p- allel and distributed computer systems, sensor fusion, fractal engineering), de- sion analysis and systems, economics, electrical engineering (e.g., control, signal analysis, power systems), environmental studies, informatics, medicine, mole- lar biology, musicology, neurology, robotics, social science, software engineering, spatial visualization, Web engineering, and Web mining.
    Note: Plenary Papers -- Theory -- Logic and Rough Sets -- Granular Computing -- Rough and Fuzzy Relations -- Foundations of Data Mining -- Incomplete Information Systems -- Interestingness -- Multiagents and Information Systems -- Fuzzy Logic and Modeling -- Rough Classification -- Rough Sets and Probabilities -- Variable Precision Rough Set Model -- Spatial Reasoning -- Reduction -- Rule Induction -- Rough Sets and Neural Network -- Clustering -- Data Mining -- Image and Signal Recognition -- Information Retrieval -- Decision Support -- Adaptive and Opminization Methods -- Bioinformatics -- Medical Applications -- Bibliography Project of International Rough Set Society.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783540221173
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    UID:
    almahu_9948621571202882
    Format: XX, 860 p. , online resource.
    Edition: 1st ed. 2004.
    ISBN: 9783540259299
    Series Statement: Lecture Notes in Artificial Intelligence ; 3066
    Content: In recent years rough set theory has attracted the attention of many researchers and practitioners all over the world, who have contributed essentially to its development and applications. Weareobservingagrowingresearchinterestinthefoundationsofroughsets, including the various logical, mathematical and philosophical aspects of rough sets. Some relationships have already been established between rough sets and other approaches, and also with a wide range of hybrid systems. As a result, rough sets are linked with decision system modeling and analysis of complex systems, fuzzy sets, neural networks, evolutionary computing, data mining and knowledge discovery, pattern recognition, machine learning, and approximate reasoning. In particular, rough sets are used in probabilistic reasoning, granular computing (including information granule calculi based on rough mereology), intelligent control, intelligent agent modeling, identi?cation of autonomous s- tems, and process speci?cation. Methods based on rough set theory alone or in combination with other - proacheshavebeendiscoveredwith awide rangeofapplicationsinsuchareasas: acoustics, bioinformatics, business and ?nance, chemistry, computer engineering (e.g., data compression, digital image processing, digital signal processing, p- allel and distributed computer systems, sensor fusion, fractal engineering), de- sion analysis and systems, economics, electrical engineering (e.g., control, signal analysis, power systems), environmental studies, informatics, medicine, mole- lar biology, musicology, neurology, robotics, social science, software engineering, spatial visualization, Web engineering, and Web mining.
    Note: Plenary Papers -- Theory -- Logic and Rough Sets -- Granular Computing -- Rough and Fuzzy Relations -- Foundations of Data Mining -- Incomplete Information Systems -- Interestingness -- Multiagents and Information Systems -- Fuzzy Logic and Modeling -- Rough Classification -- Rough Sets and Probabilities -- Variable Precision Rough Set Model -- Spatial Reasoning -- Reduction -- Rule Induction -- Rough Sets and Neural Network -- Clustering -- Data Mining -- Image and Signal Recognition -- Information Retrieval -- Decision Support -- Adaptive and Opminization Methods -- Bioinformatics -- Medical Applications -- Bibliography Project of International Rough Set Society.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9783662187296
    Additional Edition: Printed edition: ISBN 9783540221173
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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