SIMULATING AN EVOLUTION STRATEGY TO FORECAST TIME SERIES ARMA(1,1) MODEL

This paper presents a multi-member evolution strategy ( ) ES   to forecast future value of observed time series ARMA(1,1) model. The proposed method is simple and straight forward and doesn t required any problem specific parameter tuning of the problem. The experiments designed based on simulate ( ) ES   for different values of sample size (n=25,50,100),model parameters  set ( 0.05,0.3,75 ) and  set to ( 0.1,0.4,.9 ) and use lead time for forecasting future value equal to (l=1,2,3).The value of  , take equal to (15,100) beside this, there is anther experiment designed for simulating one of method which is known as Box – Jenkins with same values of sample size, model parameters and leads time(l) for number of replicate (RR=1000). Results of this study has cleared by numbers of figures and tables, which are made to clear compression between ES-algorithm and B.J method based on computing values of FMSE (Forecasting Mean Square Error ) Thiels (U- statistic) ,statistics used as tools to measures reliability of ES- algorithm and also used to clear accuracy of ES algorithm results. Table(1), tables (2-7) and figures (4 -9) results of statistics show the reliability of( ) ES   algorithm to producing individuals which give reasonably predictions of future values of time series for different values of sample size and lead time values of model parameters