gavindiaz/Population-optimization-algorithms-MQL5
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modify TSEA

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This commit is contained in:
JQSakaJoo
2024-04-30 16:04:43 +05:00
parent 314ef87bcc
commit bcf8ee834d
3 changed files with 71 additions and 27 deletions
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MQL5/Include/Math/AOs/PopulationAO/#C_AO_enum.mqh
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MQL5/Include/Math/AOs/PopulationAO/AO_TSEA_TurtleShellEvolutionAlgorithm.mqh
+68 -24
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@@ -319,7 +319,7 @@ class C_AO_TSEA : public C_AO
popSize = 100; //population size
vClusters = 3; //number of vertical clusters
hClusters = 10; //number of horizontal clusters
hClusters = 20; //number of horizontal clusters
neighbNumb = 5; //number of nearest neighbors
maxAgentsInCell = 3; //max agents in cell
@@ -466,39 +466,83 @@ void C_AO_TSEA::Moving ()
for (int i = 0; i < popSize; i++)
{
while (true)
if (u.RNDprobab () < 0.8)
{
rnd = u.RNDprobab ();
rnd = (-rnd * rnd + 1.0) * vClusters;
while (true)
{
rnd = u.RNDprobab ();
rnd = (-rnd * rnd + 1.0) * vClusters;
vPos = (int)rnd;
if (vPos > vClusters - 1) vPos = vClusters - 1;
vPos = (int)rnd;
if (vPos > vClusters - 1) vPos = vClusters - 1;
hPos = u.RNDminusOne (hClusters);
hPos = u.RNDminusOne (hClusters);
size = ArraySize (cell [vPos].cell [hPos].agent);
size = ArraySize (cell [vPos].cell [hPos].agent);
if (size > 0) break;
if (size > 0) break;
}
pos = u.RNDminusOne (size);
if (u.RNDprobab () < 0.5) pos = cell [vPos].cell [hPos].indBest;
for (int c = 0; c < coords; c++)
{
if (u.RNDprobab () < 0.6) val = cell [vPos].cell [hPos].agent [pos].c [c];
else val = cB [c];
double dist = (rangeMax [c] - rangeMin [c]) * 0.1;
min = val - dist; if (min < rangeMin [c]) min = rangeMin [c];
max = val + dist; if (max > rangeMax [c]) max = rangeMax [c];
val = u.PowerDistribution (val, min, max, 30);
a [i].c [c] = u.SeInDiSp (val, rangeMin [c], rangeMax [c], rangeStep [c]);
agent [i].c [c] = a [i].c [c];
}
}
pos = u.RNDminusOne (size);
if (u.RNDprobab () < 0.5) pos = cell [vPos].cell [hPos].indBest;
for (int c = 0; c < coords; c++)
else
{
if (u.RNDprobab () < 0.6) val = cell [vPos].cell [hPos].agent [pos].c [c];
else val = cB [c];
int size2 = 0;
int hPos2 = 0;
int pos2 = 0;
double dist = (rangeMax [c] - rangeMin [c]) * 0.1;
min = val - dist; if (min < rangeMin [c]) min = rangeMin [c];
max = val + dist; if (max > rangeMax [c]) max = rangeMax [c];
while (true)
{
rnd = u.RNDprobab ();
rnd = (-rnd * rnd + 1.0) * vClusters;
val = u.PowerDistribution (val, min, max, 30);
vPos = (int)rnd;
if (vPos > vClusters - 1) vPos = vClusters - 1;
a [i].c [c] = u.SeInDiSp (val, rangeMin [c], rangeMax [c], rangeStep [c]);
hPos = u.RNDminusOne (hClusters);
agent [i].c [c] = a [i].c [c];
size = ArraySize (cell [vPos].cell [hPos].agent);
hPos2 = u.RNDminusOne (hClusters);
size2 = ArraySize (cell [vPos].cell [hPos2].agent);
if (size > 0 && size2 > 0) break;
}
pos = u.RNDminusOne (size);
pos2 = u.RNDminusOne (size2);
for (int c = 0; c < coords; c++)
{
val = (cell [vPos].cell [hPos ].agent [pos ].c [c] +
cell [vPos].cell [hPos2].agent [pos2].c [c]) * 0.5;
a [i].c [c] = u.SeInDiSp (val, rangeMin [c], rangeMax [c], rangeStep [c]);
agent [i].c [c] = a [i].c [c];
}
}
}
}
@@ -571,7 +615,7 @@ void C_AO_TSEA::Revision ()
{
agent [i].label = km.KNN (data, agent [i], neighbNumb, hClusters);
}
if (epochsNow % 50 == 0)
{
//km.KMeansPlusPlusInit (data, ArraySize (data), clusters);