MultiGrid-Based Fuzzy Systems for Time Series Forecasting: Overcoming the curse of dimensionality

摘要

This work introduces a modified Grid Based Fuzzy System architecture, which is especially suited for the problem of time series prediction. This new architecture overcomes the problem inherent to all grid-based fuzzy systems when dealing with high dimensional input data. This new architecture together with the proposed algorithm allows the possibility of incorporating a higher number of input variables, keeping low both the computational complexity of the algorithm and the complexity of the architecture.