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An improved method was proposed in order to accelerate the convergence speed and reduce the training time of back propagation (BP) neural network. The principal component analysis (PCA) was used as the pre-processing to select principal components from the input variables. The regression and correlation analysis were used as the post-processing to analyze the result and test the precision of training...
A new method for the discrimination of peach varieties by Vis/near infrared reflectance spectroscopy (NIRS) (325-1075nm) was developed. A relationship has been established between the reflectance spectra and peach varieties. The set was consisted of a total of 90 samples of peaches. First, the data was analyzed by principal component analysis (PCA). PCA compressed thousands of spectral data into a...
BP neural network is a nonlinear dynamical system widely-used in forecasting target values influenced by diverse variables. Its redundant input nodes often generate imprecision in the predict results. By introducing rough set and grey relation theories, condition attributes were considered as correlation sequences and decision attributes as reference sequences. The grey correlation coefficients represented...
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