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- W2373162059 abstract "To resolve the problem of the mismatching of model structure and data distribution as well as the problem of determining model parameters difficultly in the traditional general regression neural network(GRNN),a scheme is proposed to design a parameter-optimized rotated general regression neural network.Through the coordinate rotation,an additional parameter of model structure is introduced to the traditional general regression neural network.Moreover,the particle swarm optimization algorithm is adopted to find the best values of parameters of the rotated GRNN;hence the model precision is improved.The experimental results of two industrial applications have shown the effectiveness of the method." @default.
- W2373162059 created "2016-06-24" @default.
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- W2373162059 date "2009-01-01" @default.
- W2373162059 modified "2023-09-28" @default.
- W2373162059 title "Parameter-optimized rotated general regression neural network model" @default.
- W2373162059 hasPublicationYear "2009" @default.
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