Fuzzy Databases: Principles and Applications by Frederick E. Petry

By Frederick E. Petry

This quantity provides the result of nearly 15 years of labor from researchers world wide at the use of fuzzy set conception to symbolize imprecision in databases. The adulthood of the examine within the self-discipline and the hot advancements in commercial/industrial fuzzy databases supplied a chance to provide this survey. during this creation we'll describe in brief how fuzzy databases healthy into the final layout of database platforms after which assessment the association of the textual content. FUZZY DATABASE panorama The final 5 years were witness to a revolution within the database examine group. The dominant information versions have replaced and the consensus on what constitutes helpful examine is in flux. additionally, at the present, it's attainable to achieve a viewpoint on what has been finished within the sector of fuzzy databases. as a result, now could be an opportune time to take inventory of the earlier and identify a framework. A framework should still help in comparing destiny study via a greater figuring out of the various points of imprecision database can version [ 1 l.

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Thus the specific rows in relation r 34 Relational Databases & Fuzzy Sets Background As we have seen the domain of an attribute can be extended to include one or more null values, range values, probabilistic data entries and so forth to capture and represent various type of incomplete and uncertain data. For a situation in which the imprecision is of the sort that can best be captured by fuzzy values, domains are appropriately extended to the particular fuzzy representation. Various approaches to such extensions will be the topics of subsequent chapters.

RELATIONAL DATABASE CONCEPTS Overview In the relational model the database can be viewed as a collection of relations. As discussed in in the previous chapter each relation resembles a table or, to some extent, a simple file. In viewing a relation as a table of values, each row in the table represents a collection of related data values. These values can be interpreted as facts describing a real-world entity or relationship as captured in the entityrelationship model of our example environmental GIS.

One of the fundamental aspects of the relational model is its settheoretic basis and, as seen, a relation is defined as a set of tuples. Thus both from the definition of a set ( all elements of a set are distinct) and the need for unique accessing, all tuples in a relation must be distinct. For a tuple this implies that for any two tuples at least one of the attribute values, Vi ' must be different in both tuples. , the same combination of values for these attributes will not occur in distinct tuples.

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