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• W2016574559 abstract "This paper presents a novel artificial neural network with the Radial Basis Function (RBF) as an activation function of neurons and clustered neurons in the hidden layer which has a high learning speed, thus it is called Fast Clustered Radial Basis Function Network (FCRBFN). The weights of the network are determined by solving a number of linear equation systems. In addition, new training data can be given to the network on-line and the re-training is done at high speed using the Least Squares method. In order to test the validity of the FCRBFN, it is applied to 4 classical regression applications, and also used to build the functional adaptive predictive controller. Experimental results show that, compared with other methods, the FCRBFN with a small amount of hidden neurons could achieve good or better regression precision and generalization, as well as adaptive ability at a much faster learning speed." @default.
• W2016574559 created "2016-06-24" @default.
• W2016574559 creator A5031321641 @default.
• W2016574559 date "2015-03-01" @default.
• W2016574559 modified "2023-10-10" @default.
• W2016574559 title "Fast Clustered Radial Basis Function Network as an adaptive predictive controller" @default.
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• W2016574559 doi "https://doi.org/10.1016/j.neunet.2014.11.008" @default.
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