public CrossOver(List <Individu> individu, double crossrate, int popSize)
{
double offspring = crossrate * (double)popSize;
offspring = Math.Floor(offspring);
SqliteDatabase db = new SqliteDatabase();
DataTable dt = db.query("SELECT * FROM gejala");
rule = new List <Gejala>();
foreach (DataRow row in dt.Rows)
{
Gejala g = new Gejala();
double[] p = new double[3];
g.SetKodeGejala(Convert.ToString(row["kode_gejala"]));
g.SetNamaGejala(Convert.ToString(row["nama_gejala"]));
p[0] = Convert.ToDouble(row["pneumonia"]);
p[1] = Convert.ToDouble(row["bronkitis"]);
p[2] = Convert.ToDouble(row["urti"]);
g.SetPenyakit(p);
rule.Add(g);
}
Density de = new Density(rule);
de.setMinMax(-0.25, 0.25);
Individu alpha = new Individu(de.GetDensity());
crossover = new List <Individu>();
int[] randomIndividu = generateNumber(individu.Count);
int offset = 0;
while (crossover.Count < offspring)
{
List <Gejala> c = new List <Gejala>();
c = Cross(individu[offset], individu[offset + 1], alpha);
Individu v = new Individu(c);
crossover.Add(v);
if (crossover.Count < offspring)
{
c = Cross(individu[offset + 1], individu[offset], alpha);
Individu v2 = new Individu(c);
crossover.Add(v2);
offset = offset + 2;
}
}
}
public CrossOver(List<Individu> individu, double crossrate, int popSize)
{
double offspring = crossrate * (double) popSize;
offspring = Math.Floor(offspring);
SqliteDatabase db = new SqliteDatabase();
DataTable dt = db.query("SELECT * FROM gejala");
rule = new List<Gejala>();
foreach (DataRow row in dt.Rows)
{
Gejala g = new Gejala();
double[] p = new double[3];
g.SetKodeGejala(Convert.ToString(row["kode_gejala"]));
g.SetNamaGejala(Convert.ToString(row["nama_gejala"]));
p[0] = Convert.ToDouble(row["pneumonia"]);
p[1] = Convert.ToDouble(row["bronkitis"]);
p[2] = Convert.ToDouble(row["urti"]);
g.SetPenyakit(p);
rule.Add(g);
}
Density de = new Density(rule);
de.setMinMax(-0.25, 0.25);
Individu alpha = new Individu(de.GetDensity());
crossover = new List<Individu>();
int[] randomIndividu = generateNumber(individu.Count);
int offset = 0;
while (crossover.Count < offspring)
{
List<Gejala> c = new List<Gejala>();
c = Cross(individu[offset], individu[offset + 1], alpha);
Individu v = new Individu(c);
crossover.Add(v);
if (crossover.Count < offspring)
{
c = Cross(individu[offset + 1], individu[offset], alpha);
Individu v2 = new Individu(c);
crossover.Add(v2);
offset = offset + 2;
}
}
}
public Form1()
{
InitializeComponent();
db = new SqliteDatabase();
DataTable dt = new DataTable();
dt = db.query("SELECT * FROM gejala");
List<Gejala> rule = new List<Gejala>();
double[,] cek = {
{0.534, 0.875, 0.530},
{0.238, 0.374, 0.573},
{0.468, 0, 0},
{0.375, 0.583, 0.384},
{0, 0.347, 0.474},
{0.472, 0.582, 0},
{0, 0.285, 0.372},
{0, 0.514, 0.572},
{0.372, 0.512, 0},
{0.582, 0, 0},
{0, 0.352, 0},
{0, 0, 0.235},
{0.682, 0.235, 0},
{0, 0.523, 0},
{0.5325, 0, 0},
{0.5244, 0.483, 0},
{0, 0.602, 0.662}
};
List<double[]> c*k = new List<double[]>();
for (int z = 0; z < cek.GetLength(0); z++)
{
double[] fak = new double[3];
fak[0] = cek[z, 0];
fak[1] = cek[z, 1];
fak[2] = cek[z, 2];
c*k.Add(fak);
}
foreach (DataRow row in dt.Rows)
{
Gejala g = new Gejala();
double[] p = new double[3];
g.SetKodeGejala(Convert.ToString(row["kode_gejala"]));
g.SetNamaGejala(Convert.ToString(row["nama_gejala"]));
p[0] = Convert.ToDouble(row["pneumonia"]);
p[1] = Convert.ToDouble(row["bronkitis"]);
p[2] = Convert.ToDouble(row["urti"]);
g.SetPenyakit(p);
rule.Add(g);
}
List<Gejala> pesatu = new List<Gejala>();
for (int i = 0; i < rule.Count; i++)
{
Gejala h = new Gejala();
h.SetKodeGejala(rule[i].GetKodeGejala());
h.SetPenyakit(c*k[i]);
pesatu.Add(h);
}
de = new Density(rule);
p1 = new Individu(pesatu);
p2 = new Individu(de.GetDensity());
}
public Form1()
{
InitializeComponent();
db = new SqliteDatabase();
DataTable dt = new DataTable();
dt = db.query("SELECT * FROM gejala");
List <Gejala> rule = new List <Gejala>();
double[,] cek =
{
{ 0.534, 0.875, 0.530 },
{ 0.238, 0.374, 0.573 },
{ 0.468, 0, 0 },
{ 0.375, 0.583, 0.384 },
{ 0, 0.347, 0.474 },
{ 0.472, 0.582, 0 },
{ 0, 0.285, 0.372 },
{ 0, 0.514, 0.572 },
{ 0.372, 0.512, 0 },
{ 0.582, 0, 0 },
{ 0, 0.352, 0 },
{ 0, 0, 0.235 },
{ 0.682, 0.235, 0 },
{ 0, 0.523, 0 },
{ 0.5325, 0, 0 },
{ 0.5244, 0.483, 0 },
{ 0, 0.602, 0.662 }
};
List <double[]> c*k = new List <double[]>();
for (int z = 0; z < cek.GetLength(0); z++)
{
double[] fak = new double[3];
fak[0] = cek[z, 0];
fak[1] = cek[z, 1];
fak[2] = cek[z, 2];
c*k.Add(fak);
}
foreach (DataRow row in dt.Rows)
{
Gejala g = new Gejala();
double[] p = new double[3];
g.SetKodeGejala(Convert.ToString(row["kode_gejala"]));
g.SetNamaGejala(Convert.ToString(row["nama_gejala"]));
p[0] = Convert.ToDouble(row["pneumonia"]);
p[1] = Convert.ToDouble(row["bronkitis"]);
p[2] = Convert.ToDouble(row["urti"]);
g.SetPenyakit(p);
rule.Add(g);
}
List <Gejala> pesatu = new List <Gejala>();
for (int i = 0; i < rule.Count; i++)
{
Gejala h = new Gejala();
h.SetKodeGejala(rule[i].GetKodeGejala());
h.SetPenyakit(c*k[i]);
pesatu.Add(h);
}
de = new Density(rule);
p1 = new Individu(pesatu);
p2 = new Individu(de.GetDensity());
}
private void prosesBtn_Click(object sender, EventArgs e)
{
beliefDgv.Rows.Clear();
individuDgv.Rows.Clear();
int popSize = Convert.ToInt32(popSizeBox.Text);
int iterasi = Convert.ToInt32(iterationBox.Text);
double cr = Convert.ToDouble(crBox.Text);
double mr = Convert.ToDouble(mrBox.Text);
DataTable dt = db.query("SELECT * FROM gejala");
rule = new List<Gejala>();
foreach (DataRow row in dt.Rows)
{
Gejala g = new Gejala();
double[] p = new double[3];
g.SetKodeGejala(Convert.ToString(row["kode_gejala"]));
g.SetNamaGejala(Convert.ToString(row["nama_gejala"]));
p[0] = Convert.ToDouble(row["pneumonia"]);
p[1] = Convert.ToDouble(row["bronkitis"]);
p[2] = Convert.ToDouble(row["urti"]);
g.SetPenyakit(p);
rule.Add(g);
}
DataTable ks = db.query("SELECT * FROM kasus");
List<Kasus> listKasus = new List<Kasus>();
foreach (DataRow r in ks.Rows)
{
string s = Convert.ToString(r["gejala"]);
string[] gejala = Array.ConvertAll(s.Split(','), ge => ge.Trim());
string d = Convert.ToString(r["diagnosa"]);
string[] diagnosa = Array.ConvertAll(d.Split(','), di => di.Trim());
Kasus k = new Kasus();
k.SetGejala(gejala);
k.SetDiagnosa(diagnosa);
listKasus.Add(k);
}
de = new Density(rule);
iBaru = new List<Individu>();
List<int> index = new List<int>();
for (int iter = 0; iter < iterasi; iter++)
{
// Init
List<Individu> P;
Console.WriteLine("Iterasi ke - " + (iter + 1) + " ---------------------------------");
if (iter == 0)
{
P = new List<Individu>();
Console.WriteLine("-- Dempster Shafer Individu --");
for (int i = 0; i < popSize; i++)
{
Console.WriteLine(">> Individu ke - " + (i + 1));
Individu inv = new Individu(de.GetDensity());
DempsterShafer ds = new DempsterShafer(inv, listKasus);
inv.SetFitness(ds.GetFitness());
P.Add(inv);
}
}
else
{
P = iBaru;
}
List<Individu> C = new List<Individu>();
CrossOver co = new CrossOver(P, cr, popSize);
C = co.GetCrossover();
Console.WriteLine("-- Dempster Shafer Crossover --");
for (int j = 0; j < C.Count; j++)
{
Console.WriteLine(">> Crossover ke - " + (j + 1));
DempsterShafer ds = new DempsterShafer(C[j], listKasus);
C[j].SetFitness(ds.GetFitness());
}
double minimum = C[0].GetFitness();
double maximum = 0;
for (int k = 0; k < C.Count; k++)
{
if (minimum > C[k].GetFitness()) minimum = C[k].GetFitness();
if (maximum < C[k].GetFitness()) maximum = C[k].GetFitness();
}
double maxmin = maximum - minimum;
Console.WriteLine("-- Mutasi, Dempster Shafer Mutasi --");
Mutasi mts = new Mutasi(P, mr, popSize, maxmin, rule);
C.Add(mts.GetMutasi());
DempsterShafer dss = new DempsterShafer(C[C.Count - 1], listKasus);
C[C.Count - 1].SetFitness(dss.GetFitness());
Console.WriteLine("-- Nilai Fitness Akhir --");
Selection slct = new Selection(P, C, popSize);
iBaru = slct.GetITerbaik();
index = slct.GetIndex();
}
PopulateDgv(rule, iBaru[0]);
double akurasi = iBaru[0].GetFitness() * 100;
labelAkurasi.Text = akurasi.ToString() + " %";
for (int i = 0; i < iBaru.Count; i++)
{
int idIndividu = index[i]+1;
string kode;
if ( idIndividu > popSize)
{
idIndividu -= popSize;
kode = "C" + idIndividu;
}
else
{
kode = "P" + idIndividu;
}
this.individuDgv.Rows.Add(kode, iBaru[i].GetFitness());
}
MessageBox.Show("Proses Perhitungan Selesai");
}
private void prosesBtn_Click(object sender, EventArgs e)
{
beliefDgv.Rows.Clear();
individuDgv.Rows.Clear();
int popSize = Convert.ToInt32(popSizeBox.Text);
int iterasi = Convert.ToInt32(iterationBox.Text);
double cr = Convert.ToDouble(crBox.Text);
double mr = Convert.ToDouble(mrBox.Text);
DataTable dt = db.query("SELECT * FROM gejala");
rule = new List <Gejala>();
foreach (DataRow row in dt.Rows)
{
Gejala g = new Gejala();
double[] p = new double[3];
g.SetKodeGejala(Convert.ToString(row["kode_gejala"]));
g.SetNamaGejala(Convert.ToString(row["nama_gejala"]));
p[0] = Convert.ToDouble(row["pneumonia"]);
p[1] = Convert.ToDouble(row["bronkitis"]);
p[2] = Convert.ToDouble(row["urti"]);
g.SetPenyakit(p);
rule.Add(g);
}
DataTable ks = db.query("SELECT * FROM kasus");
List <Kasus> listKasus = new List <Kasus>();
foreach (DataRow r in ks.Rows)
{
string s = Convert.ToString(r["gejala"]);
string[] gejala = Array.ConvertAll(s.Split(','), ge => ge.Trim());
string d = Convert.ToString(r["diagnosa"]);
string[] diagnosa = Array.ConvertAll(d.Split(','), di => di.Trim());
Kasus k = new Kasus();
k.SetGejala(gejala);
k.SetDiagnosa(diagnosa);
listKasus.Add(k);
}
de = new Density(rule);
iBaru = new List <Individu>();
List <int> index = new List <int>();
for (int iter = 0; iter < iterasi; iter++)
{
// Init
List <Individu> P;
Console.WriteLine("Iterasi ke - " + (iter + 1) + " ---------------------------------");
if (iter == 0)
{
P = new List <Individu>();
Console.WriteLine("-- Dempster Shafer Individu --");
for (int i = 0; i < popSize; i++)
{
Console.WriteLine(">> Individu ke - " + (i + 1));
Individu inv = new Individu(de.GetDensity());
DempsterShafer ds = new DempsterShafer(inv, listKasus);
inv.SetFitness(ds.GetFitness());
P.Add(inv);
}
}
else
{
P = iBaru;
}
List <Individu> C = new List <Individu>();
CrossOver co = new CrossOver(P, cr, popSize);
C = co.GetCrossover();
Console.WriteLine("-- Dempster Shafer Crossover --");
for (int j = 0; j < C.Count; j++)
{
Console.WriteLine(">> Crossover ke - " + (j + 1));
DempsterShafer ds = new DempsterShafer(C[j], listKasus);
C[j].SetFitness(ds.GetFitness());
}
double minimum = C[0].GetFitness();
double maximum = 0;
for (int k = 0; k < C.Count; k++)
{
if (minimum > C[k].GetFitness())
{
minimum = C[k].GetFitness();
}
if (maximum < C[k].GetFitness())
{
maximum = C[k].GetFitness();
}
}
double maxmin = maximum - minimum;
Console.WriteLine("-- Mutasi, Dempster Shafer Mutasi --");
Mutasi mts = new Mutasi(P, mr, popSize, maxmin, rule);
C.Add(mts.GetMutasi());
DempsterShafer dss = new DempsterShafer(C[C.Count - 1], listKasus);
C[C.Count - 1].SetFitness(dss.GetFitness());
Console.WriteLine("-- Nilai Fitness Akhir --");
Selection slct = new Selection(P, C, popSize);
iBaru = slct.GetITerbaik();
index = slct.GetIndex();
}
PopulateDgv(rule, iBaru[0]);
double akurasi = iBaru[0].GetFitness() * 100;
labelAkurasi.Text = akurasi.ToString() + " %";
for (int i = 0; i < iBaru.Count; i++)
{
int idIndividu = index[i] + 1;
string kode;
if (idIndividu > popSize)
{
idIndividu -= popSize;
kode = "C" + idIndividu;
}
else
{
kode = "P" + idIndividu;
}
this.individuDgv.Rows.Add(kode, iBaru[i].GetFitness());
}
MessageBox.Show("Proses Perhitungan Selesai");
}