RBF neural network optimization method based on improved particle swarm optimization
A technology for improving particle swarm and neural network, applied in the field of RBF neural network optimization based on improved particle swarm algorithm, can solve the problem of local optimal convergence speed of PSO algorithm, avoid falling into local optimal, enhance accuracy and stability, good adaptability
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[0038] Exemplary embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the specific implementations shown and described in the drawings are only exemplary, and are intended to illustrate the application principle of the present invention, not to limit the application scope of the present invention.
[0039] The invention discloses an RBF neural network optimization method based on an improved particle swarm algorithm, figure 2 The topology of the RBF neural network is given, and the RBF neural network model for sea clutter prediction is used as an example to illustrate, figure 1 The specific steps of this embodiment are given:
[0040] Step 1: Determine the topology of the RBF neural network. The RBF neural network is a simple three-layer structure, in which the number of nodes in the input and output layers is determined by specific problems, and the number of hidden layers is generally cluster...
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