[Application of wavelet packets analysis-interpolation-RBF to the simultaneous determination of Fe, Mn, Cu and Zn in aluminous-alloy].
A new approach was proposed so that noises invisible spectra are eliminated by wavelet packets, and the specimen numbers of calibration samples are increased by linear interpolation. It can used to solve problems of few specimen numbers and many variables in simultaneous spectrophotometric determination. Thus forecasting resultant veracity is improved. The contents of Fe, Mn, Cu and Zn in aluminous-alloy was determined simultaneously by using wavelet packets analysis-linear interpolation-RBF (radial basis function) neural networks (WPA-Interp-RBF). Wavelet packets analysis can eliminate noises to a desired level. Linear interpolation makes specimenof training samples cover recognizable room better. So RBF can abstract more characteristic information and improve its performance. Relative error(RE) of sample is reduced remarkably with desired results.
Cheng
Zheng-jun
ZJ
Institute of Applied Chemistry, China West Normal University, Nanchong 637002, China.
Zhang
Yun-tao
YT