#property copyright "S.Projects"
#property link "cortex.snowcron.com"
#property indicator_separate_window
#property indicator_buffers 2
#property indicator_color1 Red
#property indicator_color2 Yellow
#property indicator_minimum 0
#property indicator_maximum 1
// indicator parameters
// To do: read parameters, including weights, from a description file
int nNocInterval = 12;
double dNocRange = 0.012;
int nNocMa = 5;
int nOutLag = 2;
int nLayers = 3;
int arrNeurons[3] = {17,5,1};
int nNumOfLags = 17;
int arrLags[17] =
{ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16 };
double arrWeights_0[305];
double arrWeights_1[90];
double arrWeights_2[6];
double arrOutput_0[ 17];
double arrOutput_1[ 5];
double dNnOutput;
double arrPattern[18] ;
int nRemoveFirst = 200;
double dE = 2.7182818;
// indicator buffers
double arrNocBuffer[ ];
double arrNnBuffer[ ];
int nExtCountedBars = 0;
//////////// ///////// ///
int init()
{
Array_init();
// drawing settings
SetIndexStyle( 0, DRAW_LINE);
SetIndexShift( 0, 0);
SetIndexEmptyValue( 0, 0.0);
SetIndexStyle( 1, DRAW_LINE);
SetIndexShift( 1, 0);
SetIndexEmptyValue( 1, 0.0);
IndicatorDigits( 4);
string strIndicatorShortName = "forex_nn";
IndicatorShortName(strIndicatorShortName);
// indicator buffers mapping
SetIndexBuffer( 0, arrNocBuffer) ;
SetIndexBuffer( 1, arrNnBuffer) ;
return(0);
}
//////////// ////////
int start()
{
nExtCountedBars = IndicatorCounted( );
if(nExtCountedBars < 0)
return(-1);
// last counted bar will be recounted
if(nExtCountedBars > 0)
nExtCountedBars--;
Noc();
ApplyNn();
return(0);
}
//////////// ///////
// For the selected period:
// CLV = ((Close - Low) - (High - Close)) / (High - Low)
void Noc()
{
int nPos = Bars - nExtCountedBars;
while(nPos > 0)
{
if(nPos > Bars - nRemoveFirst)
{
arrNocBuffer[ nPos] = 0.5;
nPos--;
continue;
}
double dClose = Close[nPos];
double dLow = Low[ArrayMinimum( Low, nNocInterval, nPos)];
double dHigh = High[ArrayMaximum( High, nNocInterval, nPos)];
arrNocBuffer[ nPos] = 0.1;
if(dHigh - dLow > dNocRange)
arrNocBuffer[ nPos] = (((dClose - dLow) - (dHigh -
dClose))
/ (dHigh - dLow)) / 2 + 0.5;
else
arrNocBuffer[ nPos] = (((dClose - dLow) - (dHigh -
dClose))
/ dNocRange) / 2 + 0.5;
nPos--;
}
if(nNocMa > 1)
Ema(arrNocBuffer) ;
}
//////////// ///////
void Ema(double& arr[])
{
double dPr = 2.0 / (nNocMa + 1);
int nPos = Bars - nExtCountedBars;
while(nPos > 0)
{
if(nPos == Bars - 2)
arrNocBuffer[ nPos + 1] = arr[nPos + 1];
arrNocBuffer[ nPos] = arr[nPos] * dPr + arrNocBuffer[ nPos +
1]
* (1 - dPr);
nPos--;
}
}
//////////// ///////
void ApplyNn()
{
int nPos = Bars - nExtCountedBars - 2;
while(nPos > 0)
{
if(nPos > Bars - nRemoveFirst)
{
arrNnBuffer[ nPos] = 0.5;
nPos--;
continue;
}
arrNnBuffer[ nPos] = 0.5;
for(int nLagNo = 0; nLagNo < nNumOfLags; nLagNo++)
arrPattern[nLagNo]
= arrNocBuffer[ nPos + arrLags[nLagNo] + nOutLag];
for(int nLayer = 0; nLayer < nLayers; nLayer++)
{
// Absolute index of the weight in an array
int nWeightIdx = 0;
for(int nNeuron = 0; nNeuron < arrNeurons[nLayer] ;
nNeuron++)
{
double dLinearCombiner = 0;
int nInputs = arrNeurons[nLayer] ;
if(nLayer != 0)
nInputs = arrNeurons[nLayer - 1];
for(int nInput = 0; nInput < nInputs; nInput++)
{
double dInput;
double dWeight;
switch(nLayer)
{
case 0:
{
dInput = arrPattern[nInput] ;
dWeight = arrWeights_0[ nWeightIdx] ;
}
break;
case 1:
{
dInput = arrOutput_0[ nInput];
dWeight = arrWeights_1[ nWeightIdx] ;
}
break;
default:
{
dInput = arrOutput_1[ nInput];
dWeight = arrWeights_2[ nWeightIdx] ;
}
break;
}
dLinearCombiner += dWeight * dInput;
nWeightIdx++ ;
}
switch(nLayer)
{
case 0:
dWeight = arrWeights_0[ nWeightIdx] ; break;
case 1:
dWeight = arrWeights_1[ nWeightIdx] ; break;
default:
dWeight = arrWeights_2[ nWeightIdx] ; break;
}
dLinearCombiner += (-1) * dWeight;
nWeightIdx++ ;
double dActivation = Activation(dLinearCombiner, 0);
switch(nLayer)
{
case 0:
arrOutput_0[ nNeuron] = dActivation; break;
case 1:
arrOutput_1[ nNeuron] = dActivation; break;
default:
dNnOutput = dActivation; break;
}
} // for all neurons
} // for all layers
arrNnBuffer[ nPos] = dNnOutput;
nPos--;
} // for all patterns
}
//////////// ///////
double Activation(double u, int nType)
{
//double dEx = TANH(u / 2);
double dPow = MathPow(dE, 2 * u / 2);
double dEx = (dPow - 1) / (dPow + 1);
if(dEx == 1 || dEx == -1)
dEx = dEx * 0.999999999;
// 0 - sigmoid, 1 - tangent
if(nType == 0)
return((dEx + 1) / 2);
return(dEx);
}
int Array_init()
{
// Layer: 0
arrWeights_0[ 0] = 0.376436;
arrWeights_0[ 1] = 0.690657;
arrWeights_0[ 2] = 0.512335;
arrWeights_0[ 3] = 0.786179;
arrWeights_0[ 4] = 0.671377;
arrWeights_0[ 5] = 0.614279;
arrWeights_0[ 6] = 0.539750;
arrWeights_0[ 7] = 0.820380;
arrWeights_0[ 8] = 0.750566;
arrWeights_0[ 9] = 0.707890;
arrWeights_0[ 10] = 0.396094;
arrWeights_0[ 11] = 0.725720;
arrWeights_0[ 12] = 0.555349;
arrWeights_0[ 13] = 0.395257;
arrWeights_0[ 14] = 0.227280;
arrWeights_0[ 15] = 0.128274;
arrWeights_0[ 16] = 0.289072;
arrWeights_0[ 17] = 0.387067;
arrWeights_0[ 18] = 0.662450;
arrWeights_0[ 19] = 1.019812;
arrWeights_0[ 20] = 0.761206;
arrWeights_0[ 21] = 0.984280;
arrWeights_0[ 22] = 0.878235;
arrWeights_0[ 23] = 0.829384;
arrWeights_0[ 24] = 0.786234;
arrWeights_0[ 25] = 1.189799;
arrWeights_0[ 26] = 1.112219;
arrWeights_0[ 27] = 1.069424;
arrWeights_0[ 28] = 0.640762;
arrWeights_0[ 29] = 0.730670;
arrWeights_0[ 30] = 0.067006;
arrWeights_0[ 31] = -0.320953;
arrWeights_0[ 32] = -0.600880;
arrWeights_0[ 33] = -0.371686;
arrWeights_0[ 34] = 0.261142;
arrWeights_0[ 35] = 0.063323;
arrWeights_0[ 36] = 0.413053;
arrWeights_0[ 37] = 0.737687;
arrWeights_0[ 38] = 0.555759;
arrWeights_0[ 39] = 0.815068;
arrWeights_0[ 40] = 0.692078;
arrWeights_0[ 41] = 0.630406;
arrWeights_0[ 42] = 0.556191;
arrWeights_0[ 43] = 0.846380;
arrWeights_0[ 44] = 0.763236;
arrWeights_0[ 45] = 0.715549;
arrWeights_0[ 46] = 0.390297;
arrWeights_0[ 47] = 0.705948;
arrWeights_0[ 48] = 0.482014;
arrWeights_0[ 49] = 0.291501;
arrWeights_0[ 50] = 0.101741;
arrWeights_0[ 51] = 0.048724;
arrWeights_0[ 52] = 0.280508;
arrWeights_0[ 53] = 0.428389;
arrWeights_0[ 54] = -6.065296;
arrWeights_0[ 55] = 0.559039;
arrWeights_0[ 56] = 1.732407;
arrWeights_0[ 57] = 2.446417;
arrWeights_0[ 58] = 2.226664;
arrWeights_0[ 59] = 1.043498;
arrWeights_0[ 60] = -0.892194;
arrWeights_0[ 61] = 0.538670;
arrWeights_0[ 62] = 1.696599;
arrWeights_0[ 63] = 2.895421;
arrWeights_0[ 64] = 1.936742;
arrWeights_0[ 65] = 0.857415;
arrWeights_0[ 66] = 1.777173;
arrWeights_0[ 67] = 1.489486;
arrWeights_0[ 68] = 0.990452;
arrWeights_0[ 69] = -0.312611;
arrWeights_0[ 70] = -2.485575;
arrWeights_0[ 71] = 5.784152;
arrWeights_0[ 72] = 0.691233;
arrWeights_0[ 73] = 1.003065;
arrWeights_0[ 74] = 0.746760;
arrWeights_0[ 75] = 0.973191;
arrWeights_0[ 76] = 0.868018;
arrWeights_0[ 77] = 0.821039;
arrWeights_0[ 78] = 0.770604;
arrWeights_0[ 79] = 1.139881;
arrWeights_0[ 80] = 1.057454;
arrWeights_0[ 81] = 1.004390;
arrWeights_0[ 82] = 0.595049;
arrWeights_0[ 83] = 0.733458;
arrWeights_0[ 84] = 0.177670;
arrWeights_0[ 85] = -0.170966;
arrWeights_0[ 86] = -0.443584;
arrWeights_0[ 87] = -0.345470;
arrWeights_0[ 88] = 0.135814;
arrWeights_0[ 89] = -0.010206;
arrWeights_0[ 90] = 0.585687;
arrWeights_0[ 91] = 1.040471;
arrWeights_0[ 92] = 0.778059;
arrWeights_0[ 93] = 0.994592;
arrWeights_0[ 94] = 0.882501;
arrWeights_0[ 95] = 0.819930;
arrWeights_0[ 96] = 0.783313;
arrWeights_0[ 97] = 1.225092;
arrWeights_0[ 98] = 1.138965;
arrWeights_0[ 99] = 1.112052;
arrWeights_0[ 100] = 0.667895;
arrWeights_0[ 101] = 0.725504;
arrWeights_0[ 102] = -0.042205;
arrWeights_0[ 103] = -0.470107;
arrWeights_0[ 104] = -0.758346;
arrWeights_0[ 105] = -0.356139;
arrWeights_0[ 106] = 0.477461;
arrWeights_0[ 107] = 0.159831;
arrWeights_0[ 108] = 0.465873;
arrWeights_0[ 109] = 0.827723;
arrWeights_0[ 110] = 0.635881;
arrWeights_0[ 111] = 0.876557;
arrWeights_0[ 112] = 0.751904;
arrWeights_0[ 113] = 0.689548;
arrWeights_0[ 114] = 0.624036;
arrWeights_0[ 115] = 0.943642;
arrWeights_0[ 116] = 0.844483;
arrWeights_0[ 117] = 0.793347;
arrWeights_0[ 118] = 0.439269;
arrWeights_0[ 119] = 0.710473;
arrWeights_0[ 120] = 0.362673;
arrWeights_0[ 121] = 0.107347;
arrWeights_0[ 122] = -0.123129;
arrWeights_0[ 123] = -0.079149;
arrWeights_0[ 124] = 0.300953;
arrWeights_0[ 125] = 0.333110;
arrWeights_0[ 126] = 36.878339;
arrWeights_0[ 127] = -34.157785;
arrWeights_0[ 128] = 13.570499;
arrWeights_0[ 129] = -9.445193;
arrWeights_0[ 130] = 5.906855;
arrWeights_0[ 131] = -2.631383;
arrWeights_0[ 132] = -3.466850;
arrWeights_0[ 133] = 1.387212;
arrWeights_0[ 134] = 1.168750;
arrWeights_0[ 135] = -1.252440;
arrWeights_0[ 136] = -4.167107;
arrWeights_0[ 137] = 7.462264;
arrWeights_0[ 138] = 4.218665;
arrWeights_0[ 139] = -10.616881;
arrWeights_0[ 140] = 2.816792;
arrWeights_0[ 141] = -0.854816;
arrWeights_0[ 142] = 0.465124;
arrWeights_0[ 143] = 3.805423;
arrWeights_0[ 144] = 17.371809;
arrWeights_0[ 145] = -10.758329;
arrWeights_0[ 146] = 4.288758;
arrWeights_0[ 147] = -3.300900;
arrWeights_0[ 148] = -1.387066;
arrWeights_0[ 149] = -0.545407;
arrWeights_0[ 150] = -0.627846;
arrWeights_0[ 151] = 0.359405;
arrWeights_0[ 152] = -0.910465;
arrWeights_0[ 153] = 1.672222;
arrWeights_0[ 154] = -1.087077;
arrWeights_0[ 155] = 1.711690;
arrWeights_0[ 156] = 1.892743;
arrWeights_0[ 157] = 1.370835;
arrWeights_0[ 158] = -1.074922;
arrWeights_0[ 159] = -2.069598;
arrWeights_0[ 160] = 2.132245;
arrWeights_0[ 161] = 3.323435;
arrWeights_0[ 162] = 3.192245;
arrWeights_0[ 163] = 0.722216;
arrWeights_0[ 164] = 0.595036;
arrWeights_0[ 165] = 2.562026;
arrWeights_0[ 166] = 4.118245;
arrWeights_0[ 167] = 2.533825;
arrWeights_0[ 168] = 0.661547;
arrWeights_0[ 169] = -0.522384;
arrWeights_0[ 170] = -0.923482;
arrWeights_0[ 171] = -0.744284;
arrWeights_0[ 172] = -0.531758;
arrWeights_0[ 173] = -1.737114;
arrWeights_0[ 174] = -0.894963;
arrWeights_0[ 175] = 0.335197;
arrWeights_0[ 176] = 2.767129;
arrWeights_0[ 177] = 0.169424;
arrWeights_0[ 178] = -1.868230;
arrWeights_0[ 179] = 2.057215;
arrWeights_0[ 180] = 0.408584;
arrWeights_0[ 181] = 0.730536;
arrWeights_0[ 182] = 0.549013;
arrWeights_0[ 183] = 0.810092;
arrWeights_0[ 184] = 0.687577;
arrWeights_0[ 185] = 0.626130;
arrWeights_0[ 186] = 0.551439;
arrWeights_0[ 187] = 0.839836;
arrWeights_0[ 188] = 0.758454;
arrWeights_0[ 189] = 0.711269;
arrWeights_0[ 190] = 0.388133;
arrWeights_0[ 191] = 0.706349;
arrWeights_0[ 192] = 0.491137;
arrWeights_0[ 193] = 0.305519;
arrWeights_0[ 194] = 0.119262;
arrWeights_0[ 195] = 0.059367;
arrWeights_0[ 196] = 0.280111;
arrWeights_0[ 197] = 0.432421;
arrWeights_0[ 198] = 11.382900;
arrWeights_0[ 199] = -2.355699;
arrWeights_0[ 200] = 0.800231;
arrWeights_0[ 201] = -0.812782;
arrWeights_0[ 202] = -1.725548;
arrWeights_0[ 203] = 0.506914;
arrWeights_0[ 204] = 3.685745;
arrWeights_0[ 205] = -1.570360;
arrWeights_0[ 206] = -0.678070;
arrWeights_0[ 207] = -1.385545;
arrWeights_0[ 208] = 0.665419;
arrWeights_0[ 209] = -2.403472;
arrWeights_0[ 210] = 0.348713;
arrWeights_0[ 211] = 0.948801;
arrWeights_0[ 212] = 3.943966;
arrWeights_0[ 213] = 0.609010;
arrWeights_0[ 214] = -2.954932;
arrWeights_0[ 215] = 6.570737;
arrWeights_0[ 216] = 1.098680;
arrWeights_0[ 217] = 0.457162;
arrWeights_0[ 218] = 0.047123;
arrWeights_0[ 219] = 0.314413;
arrWeights_0[ 220] = 0.270546;
arrWeights_0[ 221] = 0.271241;
arrWeights_0[ 222] = 0.444340;
arrWeights_0[ 223] = 0.685449;
arrWeights_0[ 224] = 0.881795;
arrWeights_0[ 225] = 0.904727;
arrWeights_0[ 226] = 0.538997;
arrWeights_0[ 227] = 0.274688;
arrWeights_0[ 228] = -0.107260;
arrWeights_0[ 229] = -0.182735;
arrWeights_0[ 230] = -0.297917;
arrWeights_0[ 231] = -0.722563;
arrWeights_0[ 232] = -1.004438;
arrWeights_0[ 233] = 2.114029;
arrWeights_0[ 234] = 0.625319;
arrWeights_0[ 235] = 1.073737;
arrWeights_0[ 236] = 0.794572;
arrWeights_0[ 237] = 1.012257;
arrWeights_0[ 238] = 0.909403;
arrWeights_0[ 239] = 0.851104;
arrWeights_0[ 240] = 0.819041;
arrWeights_0[ 241] = 1.284499;
arrWeights_0[ 242] = 1.213157;
arrWeights_0[ 243] = 1.195116;
arrWeights_0[ 244] = 0.731964;
arrWeights_0[ 245] = 0.733472;
arrWeights_0[ 246] = -0.119051;
arrWeights_0[ 247] = -0.574390;
arrWeights_0[ 248] = -0.865588;
arrWeights_0[ 249] = -0.405175;
arrWeights_0[ 250] = 0.494158;
arrWeights_0[ 251] = 0.142718;
arrWeights_0[ 252] = 0.443620;
arrWeights_0[ 253] = 0.790221;
arrWeights_0[ 254] = 0.604280;
arrWeights_0[ 255] = 0.852407;
arrWeights_0[ 256] = 0.728354;
arrWeights_0[ 257] = 0.666281;
arrWeights_0[ 258] = 0.596990;
arrWeights_0[ 259] = 0.903026;
arrWeights_0[ 260] = 0.809120;
arrWeights_0[ 261] = 0.758782;
arrWeights_0[ 262] = 0.416953;
arrWeights_0[ 263] = 0.708992;
arrWeights_0[ 264] = 0.415040;
arrWeights_0[ 265] = 0.186673;
arrWeights_0[ 266] = -0.028387;
arrWeights_0[ 267] = -0.027435;
arrWeights_0[ 268] = 0.289143;
arrWeights_0[ 269] = 0.376176;
arrWeights_0[ 270] = 0.377669;
arrWeights_0[ 271] = 0.691528;
arrWeights_0[ 272] = 0.513124;
arrWeights_0[ 273] = 0.786421;
arrWeights_0[ 274] = 0.670892;
arrWeights_0[ 275] = 0.613345;
arrWeights_0[ 276] = 0.538605;
arrWeights_0[ 277] = 0.819386;
arrWeights_0[ 278] = 0.749119;
arrWeights_0[ 279] = 0.706133;
arrWeights_0[ 280] = 0.394004;
arrWeights_0[ 281] = 0.723393;
arrWeights_0[ 282] = 0.551766;
arrWeights_0[ 283] = 0.390955;
arrWeights_0[ 284] = 0.222564;
arrWeights_0[ 285] = 0.125193;
arrWeights_0[ 286] = 0.287931;
arrWeights_0[ 287] = 0.397175;
arrWeights_0[ 288] = 0.390177;
arrWeights_0[ 289] = 0.704718;
arrWeights_0[ 290] = 0.524964;
arrWeights_0[ 291] = 0.793337;
arrWeights_0[ 292] = 0.673926;
arrWeights_0[ 293] = 0.614109;
arrWeights_0[ 294] = 0.538623;
arrWeights_0[ 295] = 0.821537;
arrWeights_0[ 296] = 0.747044;
arrWeights_0[ 297] = 0.702102;
arrWeights_0[ 298] = 0.386249;
arrWeights_0[ 299] = 0.712341;
arrWeights_0[ 300] = 0.526445;
arrWeights_0[ 301] = 0.357474;
arrWeights_0[ 302] = 0.183363;
arrWeights_0[ 303] = 0.099539;
arrWeights_0[ 304] = 0.282065;
arrWeights_0[ 305] = 0.431269;
// Layer: 1
arrWeights_1[ 0] = 0.313367;
arrWeights_1[ 1] = 0.600233;
arrWeights_1[ 2] = 0.413307;
arrWeights_1[ 3] = 0.723853;
arrWeights_1[ 4] = 0.604417;
arrWeights_1[ 5] = 0.564724;
arrWeights_1[ 6] = 0.494233;
arrWeights_1[ 7] = 0.776964;
arrWeights_1[ 8] = 0.713700;
arrWeights_1[ 9] = 0.689037;
arrWeights_1[ 10] = 0.403412;
arrWeights_1[ 11] = 0.743660;
arrWeights_1[ 12] = 0.681661;
arrWeights_1[ 13] = 0.582135;
arrWeights_1[ 14] = 0.470205;
arrWeights_1[ 15] = 0.320594;
arrWeights_1[ 16] = 0.360557;
arrWeights_1[ 17] = 0.505358;
arrWeights_1[ 18] = 0.207009;
arrWeights_1[ 19] = -0.600315;
arrWeights_1[ 20] = 0.292799;
arrWeights_1[ 21] = -0.486397;
arrWeights_1[ 22] = -0.698483;
arrWeights_1[ 23] = -0.466675;
arrWeights_1[ 24] = 0.161680;
arrWeights_1[ 25] = 1.267072;
arrWeights_1[ 26] = 0.942115;
arrWeights_1[ 27] = 1.601429;
arrWeights_1[ 28] = 0.294829;
arrWeights_1[ 29] = 2.066898;
arrWeights_1[ 30] = 1.149577;
arrWeights_1[ 31] = -0.608109;
arrWeights_1[ 32] = 0.236174;
arrWeights_1[ 33] = 0.223691;
arrWeights_1[ 34] = 0.281142;
arrWeights_1[ 35] = 2.639872;
arrWeights_1[ 36] = 0.298441;
arrWeights_1[ 37] = 0.585156;
arrWeights_1[ 38] = 0.397331;
arrWeights_1[ 39] = 0.714002;
arrWeights_1[ 40] = 0.591642;
arrWeights_1[ 41] = 0.547087;
arrWeights_1[ 42] = 0.477829;
arrWeights_1[ 43] = 0.768086;
arrWeights_1[ 44] = 0.709662;
arrWeights_1[ 45] = 0.679375;
arrWeights_1[ 46] = 0.387499;
arrWeights_1[ 47] = 0.736123;
arrWeights_1[ 48] = 0.665259;
arrWeights_1[ 49] = 0.564510;
arrWeights_1[ 50] = 0.453956;
arrWeights_1[ 51] = 0.305558;
arrWeights_1[ 52] = 0.345016;
arrWeights_1[ 53] = 0.508310;
arrWeights_1[ 54] = -0.677255;
arrWeights_1[ 55] = -1.032676;
arrWeights_1[ 56] = -0.744642;
arrWeights_1[ 57] = -0.925155;
arrWeights_1[ 58] = -1.197128;
arrWeights_1[ 59] = -0.992372;
arrWeights_1[ 60] = -0.855172;
arrWeights_1[ 61] = 7.016197;
arrWeights_1[ 62] = 5.226784;
arrWeights_1[ 63] = 2.411577;
arrWeights_1[ 64] = -0.733721;
arrWeights_1[ 65] = 3.402664;
arrWeights_1[ 66] = 1.729731;
arrWeights_1[ 67] = -0.991801;
arrWeights_1[ 68] = -0.815011;
arrWeights_1[ 69] = -0.677321;
arrWeights_1[ 70] = -0.693829;
arrWeights_1[ 71] = 9.138765;
arrWeights_1[ 72] = -0.246490;
arrWeights_1[ 73] = -0.391846;
arrWeights_1[ 74] = -0.347720;
arrWeights_1[ 75] = -1.096698;
arrWeights_1[ 76] = -0.001496;
arrWeights_1[ 77] = -0.693606;
arrWeights_1[ 78] = -0.468658;
arrWeights_1[ 79] = 6.178259;
arrWeights_1[ 80] = 4.306803;
arrWeights_1[ 81] = 2.409460;
arrWeights_1[ 82] = -0.336563;
arrWeights_1[ 83] = 2.374341;
arrWeights_1[ 84] = 1.504236;
arrWeights_1[ 85] = -0.726152;
arrWeights_1[ 86] = -0.426187;
arrWeights_1[ 87] = -0.254840;
arrWeights_1[ 88] = -0.293797;
arrWeights_1[ 89] = -1.892730;
// Layer: 2
arrWeights_2[ 0] = -0.626160;
arrWeights_2[ 1] = 1.717378;
arrWeights_2[ 2] = -0.485501;
arrWeights_2[ 3] = 2.751261;
arrWeights_2[ 4] = 2.323994;
arrWeights_2[ 5] = 2.047616;
}
Sample
Analysis
Market Information Used:
Series array that contains close prices for each bar
Series array that contains the lowest prices of each bar
Series array that contains the highest prices of each bar
Indicator Curves created:
Implements a curve of type DRAW_LINE
Indicators Used:
Custom Indicators Used:
Order Management characteristics:
Other Features: