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Fuzzy Database Modeling of Imprecise and Uncertain Engineering Information (Hardcover, 2006 ed.)
Loot Price: R2,915
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Fuzzy Database Modeling of Imprecise and Uncertain Engineering Information (Hardcover, 2006 ed.)
Series: Studies in Fuzziness and Soft Computing, 195
Expected to ship within 10 - 15 working days
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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.
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