Adaptive Forecasting of Non-Stationary Nonlinear Time Series Based on the Evolving Weighted Neuro-Neo-Fuzzy-ANARX-Model
نویسندگان
چکیده
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. It’s based on neo-fuzzy elements. 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. Index Terms — Computational Intelligence, time series prediction, neuro-neo-fuzzy System, Machine Learning, ANARX, Data Stream.
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ورودعنوان ژورنال:
- CoRR
دوره abs/1610.06486 شماره
صفحات -
تاریخ انتشار 2016