Medical applications of artificial neural networks: connectionist models of survival
Medical applications of artificial neural networks: connectionist models of survival
Time-series forecasting using flexible neural tree model
Information Sciences: an International Journal
Multiscale approximation with hierarchical radial basis functions networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Cascaded and hierarchical neural networks for classifying surface images of marble slabs
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
ICA Based on KPCA and Hierarchical RBF Network for Face Recognition
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Hi-index | 0.00 |
The purpose of this study is to identify the hierarchical radial basis function neural networks and select important input features for each sub-RBF neural network automatically. Based on the pre-defined instruction/operator sets, a hierarchical RBF neural network can be created and evolved by using tree-structure based evolutionary algorithm. This framework allows input variables selection, over-layer connections for the various nodes involved. The HRBF structure is developed using an evolutionary algorithm and the parameters are optimized by particle swarm optimization algorithm. Empirical results on benchmark classification problems indicate that the proposed method is efficient.