NEURAL NETWORK PREDICTION OF THE TIME SERIES, CONSISTED OF HOURLY VALUES OF ELECTRICITY PRICES ON THE RUSSIAN WHOLESALE ELECTRICITY MARKET
The article presents the results of an artificial neural network (ANN) prediction of the time series (TS), consisted of hourly values of electricity prices on the Russian wholesale electricity market. According to the experiments, ANN (the multilayer perceptron) parameters should be chosen considering time series features. The obtained results show that the highest accuracy is reached if a number of output neurons (number of predicted points) is equal to a TS period of a one week. ANN with the best result was used to predict TS values between 01.01.2014 and 20.04.2014. Two prediction techniques have been used – a sequential forecast and an accumulative forecast. Results of these techniques have been compared with each other and with results presented in considered information sources. The best result was found with an accumulative forecast, were the ANN was created in according to described recommendations.