Time-series prediction by answer-in-weights neural network consisting of three fluctuation estimators

In time-series data prediction, periodic and long-term componerts are often separately handled in a pre-divided form We have investigated a neural network model that can identify the two parts, simultaneously The model consists of two parts of the network arranged in the answer-in-weights structure In this report, we propose to use an answer-in-weights network consisting of three component estimators. To show the effectiveness of the network we perform computer simulation on economic data As the result, we confirm the effectiveness of using the answer-in-weights neural network for time-series production.