Pages that link to "Item:Q5958022"
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The following pages link to Time series analysis using normalized PG-RBF network with regression weights (Q5958022):
Displaying 10 items.
- The TaSe-NF model for function approximation problems: approaching local and global modelling (Q549295) (← links)
- A hybrid algorithm to optimize RBF network architecture and parameters for nonlinear time series prediction (Q693377) (← links)
- Hybridization of intelligent techniques and ARIMA models for time series prediction (Q835085) (← links)
- Nonlinear modeling and control approach to magnetic levitation ball system using functional weight RBF network-based state-dependent ARX model (Q1660668) (← links)
- An approach for on-line extraction of fuzzy rules using a self-organising fuzzy neural network (Q1770725) (← links)
- Using radial basis function networks for function approximation and classification (Q1954367) (← links)
- A review on computational intelligence for identification of nonlinear dynamical systems (Q2023111) (← links)
- TaSe, a Taylor series-based fuzzy system model that combines interpretability and accuracy (Q2386252) (← links)
- ANNEALED CHAOTIC LEARNING FOR TIME SERIES PREDICTION IN IMPROVED NEURO-FUZZY NETWORK WITH FEEDBACKS (Q3401068) (← links)
- Modeling and Control Approach to Coupled Tanks Liquid Level System Based on Function‐Type Weight RBF‐ARX Model (Q5270476) (← links)
