//Intermediate Crossover, Predictor
Predictor Functions::intermediateCrossover(Predictor &pred1, Predictor &pred2){
scalingfactor = (float)rand()/RAND_MAX * (OFFSPRINGFACTOR*2 + 1) - OFFSPRINGFACTOR;
float a = pred1.getA() + scalingfactor*(pred2.getA() - pred1.getA());
scalingfactor = (float)rand()/RAND_MAX * (OFFSPRINGFACTOR*2 + 1) - OFFSPRINGFACTOR;
float b = pred1.getB() + scalingfactor*(pred2.getB() - pred1.getB());
scalingfactor = (float)rand()/RAND_MAX * (OFFSPRINGFACTOR*2 + 1) - OFFSPRINGFACTOR;
float c = pred1.getC() + scalingfactor*(pred2.getC() - pred1.getC());
scalingfactor = (float)rand()/RAND_MAX * (OFFSPRINGFACTOR*2 + 1) - OFFSPRINGFACTOR;
float d = pred1.getD() + scalingfactor*(pred2.getD() - pred1.getD());
return Predictor(a,b,c,d);
}
//Real Valued Mutation, Predictor
Predictor Functions::realValuedMutation(Predictor &predictor){
float s[2] = {-1, 1};
float u[2] = {0, 1};
float si = s[(int)rand()%2];
float ri = MUTATIONRANGE*10;
float ai = pow(2,-u[(int)rand()%2]*MUTATIONPRECISION );
float a = predictor.getA() + (si * ri * ai);
float b = predictor.getB() + (si * ri * ai);
float c = predictor.getC() + (si * ri * ai);
float d = predictor.getD() + (si * ri * ai);
return Predictor(a,b,c,d);
}
//Polynomial Function Fitness
void Functions::fitnessPoly(Predictor &predictor){
float a = 1;
float b = 2;
float c = 3;
float d = 4;
float fitness = 0;
for(int i = 0; i < SAMPLESIZE; i++){
float x = rand()%XRANGE - (XRANGE/2); //Choosing random x's as a sample
float y1 = a*pow(x,3) + b*pow(x,2) + c*x + d;
float y2 = predictor.getA()*pow(x,3) + predictor.getB()*pow(x,2) + predictor.getC()*x + predictor.getD();
fitness += pow(y2-y1,2);
}
fitness /= SAMPLESIZE;
predictor.setFitness(fitness);
}