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A compound model PSO with stochastic inertia weight is put forward and used to optimize the parameters of wavelet neural network. The trained wavelet neural-network is applied to choosing tested position of gearbox. It is an available approach to solve the problems on extracting fault characteristic values and choosing appropriate tested positions in fault diagnosis.
A hybrid particle swarm optimization (PSO)-based wavelet neural network (WNN) for Video OCR is presented in this paper. Video OCR is an important task towards enabling automatic content-based retrieval of digital video databases. However, since text is often displayed against a complex background, its detection and extraction is a challenging problem. In this paper, wavelet transformation is done...
For the shortcoming of Particle Swarm Optimization (PSO) algorithm in Wavelet Neural Network (WNN) training, a modeling approach of WNN based on improved PSO algorithm is proposed. The approach applied a PSO algorithm based on the strategies of multi-particle information sharing and self-adaptive inertia weight to optimize the parameters of WNN for modeling quality of WNN. The experiment result indicates...
In this paper, a new automatic method for constructing and evolving complex network is proposed. This method uses the concept of complex networks (mainly scale-free networks) and combines the essence of immune programming with particle swarm optimization algorithm. The structure of a complex network genotype is evolved using immune programming algorithm with specific parameters, and the fine tuning...
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