title: [Artificial neural network applied for spectral overlap interference correction in ICP-AES].
abstract: A back-propagation artificial neural network (BP-ANN) has been applied to correcting spectral overlap interference in inductively coupled plasma atomic emission spectrometry (ICP-AES). Some network parameters including the range of input values and training sequence for training patterns presented to the network were discussed using simulated Ce 413.380nm and Pr 413.380nm line profiles. Results show that the noise in simulated mixture spectra will slow down the network convergence and has more influence on network prediction.
authors.affiliation: Department of Chemistry, Northeast Normal University, 130024 Changchun.
authors.forename: Z
authors.initials: Z
authors.lastname: Zhang
authors.forename: S
authors.initials: S
authors.lastname: Liu
authors.forename: X
authors.initials: X
authors.lastname: Zeng
mesh_terms: D016571:Neural Networks, Computer; D013054:Spectrophotometry, Atomic / Q000706:statistics & numerical data*