C++ Neural Networks and Fuzzy Logic: Preface


C++ Neural Networks and Fuzzy Logic



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C neural networks and fuzzy logic

C++ Neural Networks and Fuzzy Logic

by Valluru B. Rao

MTBooks, IDG Books Worldwide, Inc.



ISBN: 1558515526   Pub Date: 06/01/95

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The result of the operation:

PROJECT (R1 over D1) with LEVEL(D1) = 0.6

is the relation R2 given in Table 16.5.

Table 16.5 Relation R2, which is the Result of PROJECT Operation

D1

{Georgette, Ernie}

{Georgette, Grace}

Darrell


This projection operation with a condition on the level works as follows. First, the column for D1 is to be

picked, of the two columns that R1 shows. Repetitions are removed. The condition says that if two elements

of D1 have a similarity of 0.6 or higher, they should be treated as the same. Even though similarity levels of

pairs (Georgette, Ernie) and (Georgette, Grace) are both greater than 0.6, the pair (Ernie, Grace) has similarity

of 0.4 only so that we do not treat the three as the same.

This type of table is not constructed in the standard database model, so this is part of an extension of the

standard model.

Suppose you recast the information in the relation R1 and call it R3, shown in Table 16.6.



Table 16.6 Example for Relation R3, with Domains D1 and D2

D1D2

Georgette{Spanish, Italian}

Darrell{French, Spanish, Japanese}

Grace{Chinese, French}

Ernie{Russian, Spanish}

This kind of a table also is not found in standard databases (where there are groups with more than one

element used in the relation), and is an example of an extended model.


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