In this paper, we propose a training algorithm based on a novel population-based evolutionary technique, quantum-behaved particle swarm optimization (QPSO), to ...
In this paper, we propose a training algorithm based on a novel population-based evolutionary technique, quantum-behaved particle swarm optimization (QPSO), to ...
To use a RBF network, a training algorithm is absolutely necessary for determining the network parameters. The existing training algorithms, such as Orthogonal ...
Oct 22, 2024 · The proposed QPSO-Trained RBF network was test on nonlinear system identification problem, and the results show that it can identifying the ...
To use a RBF network, a training algorithm is absolutely necessary for determining the network parameters. The existing training algorithms, such as Orthogonal ...
In this paper, we make an attempt to explore the applicability of Quantum-behaved Particle Swarm Optimization, a newly proposed evolutionary search technique, ...
For training the RBFNN K-means clustering algorithm and quantum-behaved particle swarm optimization (QPSO) algorithm has been used. The K-means clustering ...
The neural network used for classification is radial basis function neural network (RBFNN). For training the RBFNN K-means clustering algorithm and quantum- ...
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For training the RBFNN K-means clustering algorithm and quantum-behaved particle swarm optimization (QPSO) algorithm has been used. The K-means clustering ...
We have used a new structure of fuzzy RBF neural network, which has been proved that it is better than other structures in term of interpretability. Our model ...