C++ Neural Networks and Fuzzy Logic: Preface

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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Queries

Let us turn our attention now to how queries are answered with this type of a database model. Suppose you

want a list of U.S. citizens in your database. Peter and Alan clearly satisfy this condition on citizenship. Andre

and Raj can only be said to possibly satisfy this condition. But Roberto and James clearly do not satisfy the

given condition. This query itself is crisp and not fuzzy (either you belong to the list of U.S. citizens or you

don’t). The answer therefore should be a crisp set, meaning that unless the degree of membership is 1, you

will not list an element. So you get the set containing Peter and Alan only.

A second query could be for people who made more than a few visits outside the United States Here the query

is fuzzy. James with many visits outside United States seems to clearly satisfy the given condition. It is

perhaps reasonable to assume that each element in the fuzzy set for many appears in the fuzzy set more than

a few with a degree of membership 1. Andre’s 2 may be a number that merits 0 degree of membership in

more than a few. The other numbers in the database are such that they possibly satisfy the given condition to

different degrees. You can see that the answer to this fuzzy query is a fuzzy set. Now, we switch gears a little,

to talk more on fuzzy theory. This will help with material to follow.