Abstract
Considering the inherent characteristics of RBF network structure, a hybrid intelligent algorithm based on hierarchical encoding strategy is proposed in this paper. This method takes LSM based on singular value decomposition to optimize the linear weights, take hierarchic genetic algorithm, which combined with Gauss–Newton descend search, immune characteristics and chaos idea, to optimize the RBF network structure and hidden layer parameters. Simulation results demonstrate it is effective and superior to some other methods.
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She, Y.G. (2012). Hybrid Intelligent Algorithm Based on Hierarchical Encoding for Training of RBF Neural Network. In: Hou, Z. (eds) Measuring Technology and Mechatronics Automation in Electrical Engineering. Lecture Notes in Electrical Engineering, vol 135. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-2185-6_33
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DOI: https://doi.org/10.1007/978-1-4614-2185-6_33
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