Chaotic Time Series Prediction using PSFS2

抄録

This paper presents a generalized parallel-structure fuzzy system (PSFS2) for prediction of chaotic time series like sunspot number data. The PSFS2 consists of a multiple number of component fuzzy systems connected in parallel. Each component fuzzy system in the PSFS2 predicts future data independently based on its past time series data with different embedding dimension and time delay. An embedding dimension determines the number of inputs of each component fuzzy system and a time delay decides the interval of inputs of the time series. According to the embedding dimension and the time delay, the component fuzzy system takes various input-output pairs. The PSFS determines the final predicted value as an average of all the outputs of the component fuzzy systems in order to reduce error accumulation effect.