Using neural nets for time series forecasting

Abstract

The purpose of the work is a comparison of statistical and neural network approaches of time series models of autoregressive moving average type construction. The basic method of research is simulation. On the basis of the results analysis, recommendations for network topology choice for neural modeling of autoregressive (AR), moving average (MA) and mixed (ARMA) processes of the various orders p, q are produced.