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A new structure adaptation algorithm for RBF networks and its application.

, and . Neural Comput. Appl., 16 (1): 91-100 (2007)

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Neural network control of multivariable processes with a fast optimisation algorithm., and . Neural Comput. Appl., 12 (3-4): 185-189 (2003)A linear parameter-varying radial basis function model and predictive control of a chemical reactor., and . Int. J. Syst. Sci., 34 (14-15): 747-761 (2003)Fault tolerant control of multivariable processes using auto-tuning PID controller., , and . IEEE Trans. Syst. Man Cybern. Part B, 35 (1): 32-43 (2005)Nonlinear Observer Fault Detection for a Multivariable Process Using a Learning Methodology., , , , and . ICAC, page 1-6. IEEE, (2018)Fault Tolerant Control of Nonlinear Processes with Adaptive Diagonal Recurrent Neural Network Model., , and . ISNN (3), volume 3498 of Lecture Notes in Computer Science, page 86-91. Springer, (2005)Development of adaptive p-step RBF network model with recursive orthogonal least squares training., , and . Neural Comput. Appl., 29 (5): 1445-1454 (2018)Factorized f-step radial basis function model for model predictive control., , , and . Neurocomputing, (2017)Air-fuel ratio prediction and NMPC for SI engines with modified Volterra model and RBF network., , , and . Eng. Appl. Artif. Intell., (2015)Friction fault diagnosis and fault tolerant control for electronic throttles with sliding mode and adaptive RBF estimator., , , , , and . J. Syst. Control. Eng., (2021)Comparative Study on Engine Torque Modelling Using Different Neural Networks., and . ISNN (3), volume 3498 of Lecture Notes in Computer Science, page 865-870. Springer, (2005)