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Fuzzy Database Modeling of Imprecise and Uncertain Engineering Information

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This book presents recent advances for imprecise and uncertain engineering information from the point of view of fuzzy database modeling. The topics include fuzzy conceptual data modeling of engineering information, conversion of the fuzzy conceptual models, and database implementation of the fuzzy conceptual data models. Some major data and database models for engineering information modeling are investigated. The main novel aspect of this book is that the book focuses on imprecise and uncertain industrial information modeling viewed from databases and fuzzy database technologies viewed from industrial applications. This may be useful for people involved in theory research, design implementation, and application development of intelligent engineering databases.

Computer-based information technologies have been extensively used to
help industries manage their processes and information systems hereby become
their nervous center. More specially, databases are designed to support
the data storage, processing, and retrieval activities related to data
management in information systems. Database management systems provide
efficient task support and database systems are the key to implementing
industrial data management. Industrial data management requires database
technique support. Industrial applications, however, are typically data
and knowledge intensive applications and have some unique characteristics
that makes their management difficult. Besides, some new techniques
such as Web, artificial intelligence, and etc. have been introduced into industrial
applications. These unique characteristics and usage of new technologies
have put many potential requirements on industrial data management,
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 management.
Much attention has been directed at conceptual data modeling of industrial
information systems. Product data models, for example, can be
views as a class of semantic data models (i.e., conceptual data models) that
take into account the needs of engineering data.
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