private void CreateInitialRandomGeneration3(int _seed)
{
//Inititally assume exponents are 0, 1, 2, 3, ... mTerms
mGenes = new Matrices.Vector <double>(Terms);
Random rand = new Random(DateTime.Now.Millisecond);
byte[] buffer = new byte[1];
int sign = 0;
for (int j = 0; j < Terms; j++)
{
for (int i = 0; i <= _seed * 2; i++)
{
rand.NextBytes(buffer);
}
sign = buffer[0] % 2;
if (sign == 0)
{
sign = -1;
}
if (MaxFuntionValue == 0 && MinFuntionValue == 0)
{
mGenes[j] = Math.Round(Math.Sqrt(rand.NextDouble()) * sign, 3);
}
else
{
mGenes[j] = rand.NextDouble() * MaxFuntionValue + MinFuntionValue;
}
}
}
public IndividualDNA(int _Terms, PointPair _MinMaxFunctionValue)
{
mTerms = _Terms;
mFitness = 0;
mGenes = new Matrices.Vector <double>(mTerms);
mError = new List <PointPair>();
mGeneration = 0;
mMinFuntionValue = _MinMaxFunctionValue.X;
mMaxFuntionValue = _MinMaxFunctionValue.Y;
}
public double GetApproximationPointValue(Matrices.Vector <double> _individual, double _x)
{
double value = 0;
for (int i = 0; i < _individual.Dimension; i++)
{
value = value + _individual[i] * Math.Pow(_x, i);
}
return(value);
}
private void CreateInitialRandomGeneration3(int _seed)
{
//Inititally assume exponents are 0, 1, 2, 3, ... mTerms
mGenes = new Matrices.Vector<double>(Terms);
Random rand = new Random(DateTime.Now.Millisecond);
byte[] buffer = new byte[1];
int sign = 0;
for (int j = 0; j < Terms; j++)
{
for (int i = 0; i <= _seed * 2; i++)
{
rand.NextBytes(buffer);
}
sign = buffer[0] % 2;
if (sign == 0) sign = -1;
if (MaxFuntionValue == 0 && MinFuntionValue == 0)
{
mGenes[j] = Math.Round(Math.Sqrt(rand.NextDouble()) * sign, 3);
}
else
{
mGenes[j] = rand.NextDouble() * MaxFuntionValue + MinFuntionValue;
}
}
}
public IndividualDNA(int _Terms, PointPair _MinMaxFunctionValue)
{
mTerms = _Terms;
mFitness = 0;
mGenes = new Matrices.Vector<double>(mTerms);
mError = new List<PointPair>();
mGeneration = 0;
mMinFuntionValue = _MinMaxFunctionValue.X;
mMaxFuntionValue = _MinMaxFunctionValue.Y;
}
