Adaptive Forecasting of Non-Stationary Nonlinear Time Series Based on   the Evolving Weighted Neuro-Neo-Fuzzy-ANARX-Model
  An evolving weighted neuro-neo-fuzzy-ANARX model and its learning procedures are introduced in the article. This system is basically used for time series forecasting. This system may be considered as a pool of elements that process data in a parallel manner. The proposed evolving system may provide online processing data streams. 
Zhengbing Hu, Yevgeniy V. Bodyanskiy, Oleksii K. Tyshchenko and Olena   O. Boiko
cs.AI cs.NE