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An approach that neural network optimized with PSO algorithm is proposed in the paper. Unlike conventional training method with gradient descent method only, this paper introduces a hybrid training algorithm by combining the PSO and BP algorithm. The PSO is used to optimize the initial parameters of the BP neural network, including the weights and biases. It can effectively better the cases that network...
The radial basis function (RBF), which is well known dynamic neural network, has been improved to easily apply in dynamic systems identification. However, the RBF weights and thresholds, which are trained by the gradient descent method, will be fixed after the training completing. The adaptive ability is bad. To improve RBF performance of dynamic identification, a self-adaptive particle swarm optimization...
The radial basis function (RBF) is well known dynamic recursion neural network. However, RBF weights and thresholds, which are trained by back propagation algorithm, the gradient descent method and genetic algorithm, will be fixed after the training completing. The adaptive ability is bad. To improve RBF identification performance, particle swarm optimization (PSO), which is a stochastic search algorithm,...
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