Multigrid-based fuzzy systems for time series prediction: CATS competition
Luis Javier Herrera, H. Pomares, Ignacio Rojas, Jesús González, Mohammed Altayeb Awad, Antonio Herrera · 2005
In this paper, the multigrid-based fuzzy system (MGFS) approach is applied for the CATS time series prediction benchmark. The MGFS architecture overcomes the problem inherent to all grid-based fuzzy systems when dealing with high dimensional input data, thus keeping low computational cost and high performance. A greedy algorithm for MGFS structure identification allows to perform the input variable selection for the time series prediction problem, while identifying the pseudo-optimal architecture according to the provided dataset.