C++ Neural Networks and Fuzzy Logic: Preface

name that identifies the category, e.g. “tight.” Various member functions are used to interface to the private

data members. There is setval(), for example, which lets you set the value of the three parameters, while

gethighval() returns the value of the parameter highval. The function getshare() returns the relative value of

membership in a category given an input. In the example discussed earlier, with the number 8.0 as the Fed

discount rate and the category tight defined according to the graph in Figure 3.2, getshare() would return 0.8.

Note that this is not yet normalized. Following this example, the getshare() value from the accommodative

category would also be used to determine the membership weights. These weights define a probability in a

given category. A random number generator is used to define a value that is used to select a fuzzy category

based on the probabilities defined.

Listing 3.1 fuzzfier.h

// fuzzfier.h V. Rao, H. Rao

// program to fuzzify data

class category

{

private:

     char name[30];

     float   lowval,highval,midval;

public:

     category(){};

     void setname(char *);

     char * getname();

     void setval(float&,float&,float&);

     float getlowval();

     float getmidval();

     float gethighval();

     float getshare(const float&);

     ~category(){};

};

int randnum(int);

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C++ Neural Networks and Fuzzy Logic:Preface

Code for the Fuzzifier

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