Fuzzy Database Modeling Imprecise by Zongmin (27 results)

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  • Language: English

    Published by Berlin, Springer, 2006

    3540306757 / 9783540306757

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    Hardcover. Condition: Wie neu. XV, 210 S.; Ill. Like new. Shrink wrapped. Sprache: Englisch Gewicht in Gramm: 600.

  • Language: English

    Published by Springer, 2006

    3540306757 / 9783540306757

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  • Language: English

    Published by Springer, 2006

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  • Language: English

    Published by Springer, 2006

    3540306757 / 9783540306757

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    Condition: New. In English.

  • Language: English

    Published by Springer, 2010

    3642067956 / 9783642067952

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    Condition: New. pp. 228.

  • Language: English

    Published by Springer, 2006

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  • Language: English

    Published by Springer Berlin Heidelberg, 2006

    3642067956 / 9783642067952

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    Paperback. Condition: Brand New. 226 pages. 9.25x6.10x0.52 inches. In Stock.

  • Language: English

    Published by Springer, 2010

    3642067956 / 9783642067952

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    Taschenbuch. Condition: Neu. Fuzzy Database Modeling of Imprecise and Uncertain Engineering Information | Zongmin Ma | Taschenbuch | Studies in Fuzziness and Soft Computing | xvi | Englisch | 2010 | Springer | EAN 9783642067952 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Language: English

    Published by Springer Berlin Heidelberg, 2010

    3642067956 / 9783642067952

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    Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Computer-based information technologies have been extensively used to help industries manage their processes and information systems hereby - come their nervous center. More specially, databases are designed to s- port the data storage, processing, and retrieval activities related to data management in information systems. Database management systems p- vide efficient task support and database systems are the key to impleme- ing industrial data management. Industrial data management requires da- base technique support. Industrial applications, however, are typically data and knowledge intensive applications and have some unique character- tics that makes their management difficult. Besides, some new techniques such as Web, artificial intelligence, and etc. have been introduced into - dustrial applications. These unique characteristics and usage of new te- nologies have put many potential requirements on industrial data mana- ment, which challenge today's database systems and promote their evolvement. Viewed from database technology, information modeling in databases can be identified at two levels: (conceptual) data modeling and (logical) database modeling. This results in conceptual (semantic) data model and logical database model. Generally a conceptual data model is designed and then the designed conceptual data model will be transformed into a chosen logical database schema. Database systems based on logical database model are used to build information systems for data mana- ment. Much attention has been directed at conceptual data modeling of - dustrial information systems. Product data models, for example, can be views as a class of semantic data models (i. e.

  • Language: English

    Published by Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2006

    3540306757 / 9783540306757

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    Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Computer-based information technologies have been extensively used to help industries manage their processes and information systems hereby - come their nervous center. More specially, databases are designed to s- port the data storage, processing, and retrieval activities related to data management in information systems. Database management systems p- vide efficient task support and database systems are the key to impleme- ing industrial data management. Industrial data management requires da- base technique support. Industrial applications, however, are typically data and knowledge intensive applications and have some unique character- tics that makes their management difficult. Besides, some new techniques such as Web, artificial intelligence, and etc. have been introduced into - dustrial applications. These unique characteristics and usage of new te- nologies have put many potential requirements on industrial data mana- ment, which challenge today's database systems and promote their evolvement. Viewed from database technology, information modeling in databases can be identified at two levels: (conceptual) data modeling and (logical) database modeling. This results in conceptual (semantic) data model and logical database model. Generally a conceptual data model is designed and then the designed conceptual data model will be transformed into a chosen logical database schema. Database systems based on logical database model are used to build information systems for data mana- ment. Much attention has been directed at conceptual data modeling of - dustrial information systems. Product data models, for example, can be views as a class of semantic data models (i. e.

  • Language: English

    Published by Springer, 2010

    3642067956 / 9783642067952

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    Condition: New. In English.

  • Language: English

    Published by Springer, 2006

    3540306757 / 9783540306757

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  • Language: English

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    Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

  • Language: English

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  • Language: English

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  • Language: English

    Published by Springer, 2010

    3642067956 / 9783642067952

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  • Language: English

    Published by Springer Berlin Heidelberg Nov 2010, 2010

    3642067956 / 9783642067952

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computer-based information technologies have been extensively used to help industries manage their processes and information systems hereby - come their nervous center. More specially, databases are designed to s- port the data storage, processing, and retrieval activities related to data management in information systems. Database management systems p- vide efficient task support and database systems are the key to impleme- ing industrial data management. Industrial data management requires da- base technique support. Industrial applications, however, are typically data and knowledge intensive applications and have some unique character- tics that makes their management difficult. Besides, some new techniques such as Web, artificial intelligence, and etc. have been introduced into - dustrial applications. These unique characteristics and usage of new te- nologies have put many potential requirements on industrial data mana- ment, which challenge today's database systems and promote their evolvement. Viewed from database technology, information modeling in databases can be identified at two levels: (conceptual) data modeling and (logical) database modeling. This results in conceptual (semantic) data model and logical database model. Generally a conceptual data model is designed and then the designed conceptual data model will be transformed into a chosen logical database schema. Database systems based on logical database model are used to build information systems for data mana- ment. Much attention has been directed at conceptual data modeling of - dustrial information systems. Product data models, for example, can be views as a class of semantic data models (i. e. 228 pp. Englisch.

  • Language: English

    Published by Springer Berlin Heidelberg Feb 2006, 2006

    3540306757 / 9783540306757

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    Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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    Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computer-based information technologies have been extensively used to help industries manage their processes and information systems hereby - come their nervous center. More specially, databases are designed to s- port the data storage, processing, and retrieval activities related to data management in information systems. Database management systems p- vide efficient task support and database systems are the key to impleme- ing industrial data management. Industrial data management requires da- base technique support. Industrial applications, however, are typically data and knowledge intensive applications and have some unique character- tics that makes their management difficult. Besides, some new techniques such as Web, artificial intelligence, and etc. have been introduced into - dustrial applications. These unique characteristics and usage of new te- nologies have put many potential requirements on industrial data mana- ment, which challenge today's database systems and promote their evolvement. Viewed from database technology, information modeling in databases can be identified at two levels: (conceptual) data modeling and (logical) database modeling. This results in conceptual (semantic) data model and logical database model. Generally a conceptual data model is designed and then the designed conceptual data model will be transformed into a chosen logical database schema. Database systems based on logical database model are used to build information systems for data mana- ment. Much attention has been directed at conceptual data modeling of - dustrial information systems. Product data models, for example, can be views as a class of semantic data models (i. e. 228 pp. Englisch.

  • Language: English

    Published by Springer Berlin Heidelberg, 2010

    3642067956 / 9783642067952

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces fuzzy database modeling advances for engineering applicationsComputer-based information technologies have been extensively used to help industries manage their processes and information systems hereby - come their nervous center. More .

  • Language: English

    Published by Springer Berlin Heidelberg, 2006

    3540306757 / 9783540306757

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces fuzzy database modeling advances for engineering applicationsComputer-based information technologies have been extensively used to help industries manage their processes and information systems hereby - come their nervous center. More .

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    3540306757 / 9783540306757

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    Condition: New. Print on Demand pp. 228 Illus.

  • Language: English

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    Condition: New. PRINT ON DEMAND pp. 228.

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    Buch. Condition: Neu. Fuzzy Database Modeling of Imprecise and Uncertain Engineering Information | Zongmin Ma | Buch | Studies in Fuzziness and Soft Computing | xvi | Englisch | 2006 | Springer | EAN 9783540306757 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

  • Language: English

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    3540306757 / 9783540306757

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    Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Computer-based information technologies have been extensively used to help industries manage their processes and information systems hereby - come their nervous center. More specially, databases are designed to s- port the data storage, processing, and retrieval activities related to data management in information systems. Database management systems p- vide efficient task support and database systems are the key to impleme- ing industrial data management. Industrial data management requires da- base technique support. Industrial applications, however, are typically data and knowledge intensive applications and have some unique character- tics that makes their management difficult. Besides, some new techniques such as Web, artificial intelligence, and etc. have been introduced into - dustrial applications. These unique characteristics and usage of new te- nologies have put many potential requirements on industrial data mana- ment, which challenge today¿s database systems and promote their evolvement. Viewed from database technology, information modeling in databases can be identified at two levels: (conceptual) data modeling and (logical) database modeling. This results in conceptual (semantic) data model and logical database model. Generally a conceptual data model is designed and then the designed conceptual data model will be transformed into a chosen logical database schema. Database systems based on logical database model are used to build information systems for data mana- ment. Much attention has been directed at conceptual data modeling of - dustrial information systems. Product data models, for example, can be views as a class of semantic data models (i. e.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 228 pp. Englisch.

  • Language: English

    Published by Springer, Springer Nov 2010, 2010

    3642067956 / 9783642067952

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Computer-based information technologies have been extensively used to help industries manage their processes and information systems hereby - come their nervous center. More specially, databases are designed to s- port the data storage, processing, and retrieval activities related to data management in information systems. Database management systems p- vide efficient task support and database systems are the key to impleme- ing industrial data management. Industrial data management requires da- base technique support. Industrial applications, however, are typically data and knowledge intensive applications and have some unique character- tics that makes their management difficult. Besides, some new techniques such as Web, artificial intelligence, and etc. have been introduced into - dustrial applications. These unique characteristics and usage of new te- nologies have put many potential requirements on industrial data mana- ment, which challenge today¿s database systems and promote their evolvement. Viewed from database technology, information modeling in databases can be identified at two levels: (conceptual) data modeling and (logical) database modeling. This results in conceptual (semantic) data model and logical database model. Generally a conceptual data model is designed and then the designed conceptual data model will be transformed into a chosen logical database schema. Database systems based on logical database model are used to build information systems for data mana- ment. Much attention has been directed at conceptual data modeling of - dustrial information systems. Product data models, for example, can be views as a class of semantic data models (i. e.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 228 pp. Englisch.