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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.
List of contents
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.
Summary
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.
Additional text
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)
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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)
