Okba Taouali, Najeh Tawfik, "Identification of Optimal Kernel Parameters of RKHS Model Based on Genetics Algorithm," WSEAS Transactions on Systems and Control, vol. 10, pp. 373-384, 2015, DOI:
Okba Taouali, Najeh Tawfik. Identification of Optimal Kernel Parameters of RKHS Model Based on Genetics Algorithm.
WSEAS Transactions on Systems and Control. 2015;10:373-384.
WSEAS Transactions on Systems and Control
Print ISSN: 1991-8763, E-ISSN: 2224-2856
Volume 10, 2015
Identification of Optimal Kernel Parameters of RKHS Model Based on Genetics Algorithm
Authors: ,
Abstract: This paper proposes a new approach based on the Genetics Algorithm to determine the optimal kernel parameters of the Reproducing Kernel Hilbert Space (RKHS) model. These parameters are the width of the kernel function and the regularization parameter. The proposed meta-method has been tested to model some benchmarks such a benchmark of DC-Motor [21], a Wiener-Hammerstein benchmark [17], a Feedback’s Process Trainer PT326 [20] and a Continuous Stirred Tank Reactor CSTR [22] and the results are satisfactory
Keywords:
RKHS, Kernel method, Regularization Networks, genetics algorithm, optimal parameters, Benchmarks model
Pages: 373-384 WSEAS Transactions on Systems and Control, ISSN / E-ISSN: 1991-8763 / 2224-2856, Volume 10, 2015, Art. #40 DOI: *As the DOI is a unique identifier, it is already available in the pdf version.
**The DOI link will be activated in the first midst of January 2026.
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