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A chaotic system identification approach based on genetic programming (GP) and multi-objective optimization is introduced. NARMAX (Nonlinear Auto Regressive Moving Average with exogenous inputs) model representation is used for the basis of the hierarchical tree encoding in GP. Criteria related to the complexity, performance and chaotic invariants obtained by chaotic time series analysis of the models...
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