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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.
Table des matières
Engineering Information Modeling in Databases.- Information Imprecision and Uncertainty in Engineering.- Fuzzy Sets and Possibility Distributions.- The Fuzzy ER/EER and UML Data Models.- The Fuzzy IDEF1X Models.- The Fuzzy EXPRESS Model.- The Fuzzy Logical Databases.- Conceptual Designs of the Fuzzy Databases.- Relational and Nested Relational Database Implementations of the Fuzzy IDEF1X and EXPRESS-G Models.- Object-Oriented Database Implementation of the Fuzzy EXPRESS Model.
Résumé
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.
Texte suppl.
From the reviews:
"The book offers a survey of fuzzy approaches to databases that serve for engineering applications. … The main value of the book is that it describes fuzzy approaches to databases in two levels: conceptual and logical. This makes the book different from other ones in this area and can be recommended to interested readers." (Jaroslav Pokorný, Zentralblatt MATH, Vol. 1125 (2), 2008)
Commentaire
From the reviews:
"The book offers a survey of fuzzy approaches to databases that serve for engineering applications. ... The main value of the book is that it describes fuzzy approaches to databases in two levels: conceptual and logical. This makes the book different from other ones in this area and can be recommended to interested readers." (Jaroslav Pokorný, Zentralblatt MATH, Vol. 1125 (2), 2008)
