Combined electromagnetism-like mechanism optimization algorithm and ROLS with D-optimality learning for RBF networks

Authors:
Fang Jia;Jun Wu
Affiliations:
Department of Control Science and Engineering, Zhejiang University, Hangzhou, Zhe Jiang, China;National Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou, China
Venue:
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part II
Year:
2010

Citing 3
Cited 0

Bayesian interpolation

Neural Computation
An Electromagnetism-like Mechanism for Global Optimization

Journal of Global Optimization
Nonlinear model structure design and construction using orthogonal least squares and D-optimality design

IEEE Transactions on Neural Networks

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Abstract

The paper proposed a new self-constructed radial basis function network designing method via a two-level learning hierarchy. Aiming at getting stronger generalization ability and robustness, an integrated algorithm which combines the regularized orthogonal least square with learning with Doptimality experimental design method was introduced at the lower level, while electromagnetism-like mechanism algorithm for global optimization was employed at the upper level to search the optimal combination of three important learning parameters, i.e., the radial basis function width, regularized parameter and D-optimality weight parameter. Through simulation results, the effectiveness of the proposed algorithm was verified.