Identification of lags in nonlinear autoregressive time series using a flexible fuzzy model
This work proposes a method to find the set of the most influential lags and the rule structure
of a Takagi–Sugeno–Kang (TSK) fuzzy model for time series applications. The proposed …
of a Takagi–Sugeno–Kang (TSK) fuzzy model for time series applications. The proposed …
Sifar: Self-identification of lags of an autoregressive tsk-based model
In this work, a Takagi-Sugeno-Kang (TSK) model is used for time series analysis and some
important questions about the identification of this kind of models are addressed: the …
important questions about the identification of this kind of models are addressed: the …
An improved fuzzy rule-based automated trading agent
H Allende-Cid, E Canessa… - 2010 XXIX International …, 2010 - ieeexplore.ieee.org
In this paper an improved Fuzzy Rule-Based Trading Agent is presented. The proposal
consists in adding machine-learning-based methods to improve the overall performance of …
consists in adding machine-learning-based methods to improve the overall performance of …