вкр_ященко (1204297), страница 6
Текст из файла (страница 6)
23 Ackley D. H., Hinton G. E., Sejnowski T. J. A learning algorithm for Bolzmann machines//Cognit. Sci. 1985. V. 9. N 1. P. 147-169.
24 Amari S. Field theory of self-organizing neural networks//IEEE Trans. Syst., Man, Cybern. 1983. V. 13. P. 741.
25 Artificial Intelligence.// Amsterdam: Time - Life - Books, 1986.
26 Athale R., Stirk C. W. Compact architectures for adaptive neuraal nets//Ibid. 1989. V. 28. N 4.
27 Bardcev S. I., Okhonin V. A. The algorithm of dual functioning (back-propagation) : general approach, vesions and applications. Krasnojarsk: Inst. of biophysics SB AS USSA - 1989.
28 Carpenter G. A., Grossberg S. A massively parallel architecture for a self-organizing neural pattern recognition machine.//Comput.Vision Graphics Image Process. 1986. V. 37. p. 54-115.
29 Cohen M. A., Grossberg S. Absolute stability of global pattern formation and parallel memory storage by competitive neural networks//IEEE Trans. Syst., Man, Cybern. 1983. V. 13. N 5.P. 815-826.
30Computing with neural circuits: a model.//Science, 1986. V. 233. p. 625-633.
31 Cross Michael. Brain ware hits Japanese computers.// New Sci. - 1988 - 120, # 1640 - p. 33.
32 Dayhoff J. Neural network architectures.//New-York: Van Nostrandreinhold, 1991. P. 141-152.
33 Fogelman Soulie F. Neural networks, state of the art, neural computing.// London: IBC Technical Services, 1991 p. 36-41.
34 Fox G. C., Koller J. G. Code generation by a generalized neural networks: general principles and elementary examples.//J. Parallel Distributed Comput. 1989. V. 6. N 2. P. 388-410.
35 Hecht-Nielsen R. Neurocomputing: picking the human brain.// IEEE SPECTRUM 1988 – V. 25. N 3 – p. 36-41.
36 Hebb D. O.The organization of behaviour. N. Y.: Wiley, 1949.
37 Hopfield J. J. Neural networks and physical systems with emergent collective computational abilities.//Proc. Natl. Acad. Sci. 1984. V. 9. p. 147-169.
38. Hopfield J. J., Tank D. W. Neural computation of decision in optimization problems.//Biol. Cybernet. 1985. V. 52. p.
39 Hopfield J. J., Feinstein D. I., Palmer F. G. Unlearning has a stabilizing effect in collective memories//Nature. 1983. V. 304. P. 141-152.
40Hopfield J. J., Tank D. W. Neural computation of decision in optimization problems//Biol. Cybernet. 1985. V. 52. P. 141-152.
41 Jeffery W., Rosner R. Neural network processing as a tool for friction optimization.//NeuronetComput. Conf., Snowbird, Utah, Apr. 13-16,1986. New York, N. Y., 1986 – p. 241-246.
42 Kuzewski Robert M., Myers Michael H., Grawford William J. Exploration of fourword error propagation as self organization structure.//IEEE Ist. Int. Conf. Neural Networks, San Diego, Calif., June 21-24,1987. V. 2. – San Diego, Calif., 1987. – p. 89-95.
43 Lippmonn Richard P. Gold Ben Neuronet classifiers useful for speech recognition.// IEEE Ist. Conf. Neural Networks, San Diego, (Calif) , 1987 – p. 417-425.
ПРИЛОЖЕНИЕА
(справочное)
Код программы на mql
Основные компоненты программы на языке MQL5
Инициализация переменных:
#include<Trade\Trade.mqh>
#include<Trade\PositionInfo.mqh>
inputdoublew0=0.5;
input double w1=0.5;
input double w2=0.5;
input double w3=0.5;
input double w4=0.5;
input double w5=0.5;
input double w6=0.5;
input double w7=0.5;
input double w8=0.5;
inputdoublew9=0.5;
intiRSI_handle;
doubleiRSI_buf[];
doubleinputs[10];
doubleweight[10];
doubleout;
stringmy_symbol;
ENUM_TIMEFRAMESmy_timeframe; //
doublelot_size;
CTradem_Trade;
CPositionInfom_Position;
externdouble Lots=0.1;
externdoubleStopLoss=180.0;
externdoubleTakeProfit=270.0;
externintFastMA=18;
externintSlowMA=36;
externintSignalMA=21;
externdouble Delta=-0.6;
externintAnnsNumber=16;
externintAnnInputs=30;
externboolNeuroFilter=true;
externboolSaveAnn=false;
externintDebugLevel=2;
externdoubleMinimalBalance=100;
externbool Parallel=true;
inputintnNeuronEntra= 35;
inputintnNeuronSal= 1;
inputint nNeuronCapa1= 45;
inputint nNeuronCapa2= 10;
Вычислительная часть программы:
start()
{
inti;
boolBuySignal=false;
boolSellSignal=false;
doubletrain_output[1];
if(!trade_allowed())
{
return(-1);
}
ann_prepare_input();
run_anns();
doubleMacdLast=iMACD(NULL,0,FastMA,SlowMA,SignalMA,PRICE_CLOSE,
MODE_MAIN,1);
doubleMacdPrev=iMACD(NULL,0,FastMA,SlowMA,SignalMA,PRICE_CLOSE,
MODE_MAIN,2);
doubleSignalLast=iMACD(NULL,0,FastMA,SlowMA,SignalMA,PRICE_CLOSE,
MODE_SIGNAL,
1);
doubleSignalPrev=iMACD(NULL,0,FastMA,SlowMA,SignalMA,PRICE_CLOSE,
MODE_SIGNAL,
2);
if(MacdLast>SignalLast&&MacdPrev<SignalPrev)
{
BuySignal=true;
}
if(MacdLast<SignalLast&&MacdPrev>SignalPrev)
{
SellSignal=true;
}
if(LongTicket==-1)
{
if(BuySignal)
{
if(!NeuroFilter || ann_wise_long()>Delta)
{
LongTicket=
OrderSend(Symbol(),OP_BUY,Lots,Ask,3,
Bid-StopLoss*Point,
Ask+TakeProfit*Point,
NAME+"-"+"L ",MagicNumber,0,Blue);
}
for(i=0;i<AnnInputs;i++)
{
LongInput[i]=InputVector[i];
}
}
} else {
OrderSelect(LongTicket,SELECT_BY_TICKET);
if(OrderCloseTime()==0)
{
if(SellSignal&&OrderProfit()>0)
{
OrderClose(LongTicket,Lots,Bid,3);
}
}
if(OrderCloseTime()!=0)
{
LongTicket=-1;
if(OrderProfit()>=0)
{
train_output[0]=1;
} else {
train_output[0]=-1;
}
for(i=0;i<AnnsNumber;i+=2)
{
ann_train(AnnsArray[i],LongInput,train_output);
}
}
}
if(ShortTicket==-1)
{
if(SellSignal)
{
if(!NeuroFilter || ann_wise_short()>Delta)
{
ShortTicket=
OrderSend(Symbol(),OP_SELL,Lots,Bid,3,
Ask+StopLoss*Point,
Bid-TakeProfit*Point,NAME+"-"+"S ",
MagicNumber,0,Red);
}
for(i=0;i<AnnInputs;i++)
{
ShortInput[i]=InputVector[i];
}
}
} else {
OrderSelect(ShortTicket,SELECT_BY_TICKET);
if(OrderCloseTime()==0)
{
// Order is opened
if(BuySignal&&OrderProfit()>0)
{
OrderClose(LongTicket,Lots,Bid,3);
}
}
if(OrderCloseTime()!=0)
{
// Order is closed
ShortTicket=-1;
if(OrderProfit()>=0)
{
train_output[0]=1;
} else {
train_output[0]=-1;
}
for(i=1;i<AnnsNumber;i+=2)
{
ann_train(AnnsArray[i],ShortInput,train_output);
}
}
}
return(0);
}















