C++ Neural Networks and Fuzzy Logic: Preface

Extending Database Models

One way of extending a model into a fuzzy model, as far as databases are concerned, is to make use of

similarity relations and to extend the operations with them as Buckles and Perry do, such as PROJECT. First

there are the domains, for the database. In our example relating to travel and tour guides above, the domains

are:

D1 = { John Smith, ... }, the set of persons included in the database,

D2 = {India, Italy, Japan, ... }, the set of countries of visit,

D3 = {Hindi, Italian, Japanese, ... }, the set of foreign languages,

D4 = {U.S., ... }, the set of countries of citizenship,

C++ Neural Networks and Fuzzy Logic:Preface

Fuzzy Queries

388

---

D5 = set of ages,

D6 = set of years,

D7 = set of number of visits,

D8 = set of length of visits.

Note that the enumerated sets are shown with ‘...’ in the sets, to indicate that there may be more entries listed,

but we are not giving a complete list. In practice, you will make a complete enumeration unlike in our

example. The domains D5, D6, D7, and D8 can also be given with all their elements listed, since in practice,

these sets are finite. Conceptually though, they are infinite sets; for example, D6 is the set of positive integers.

Next, you have the similarity relations that you define. And then there are the operations.

Example

Consider a standard database given below. It can be called also the relation R1, from set D1 = {Georgette,

Darrell, Ernie , Grace } to set D2 = {Spanish, Italian, French, Japanese, Chinese, Russian} as shown in Table

16.4: