The Research And Development Of HABC-RBF In The Fluorescence Spectrum

Artificial neural network is a kind of artificial intelligence algorithm which is proposed by simulating biological neural network, and simulated to establish a large number of simple connected artificial neural networks, and to accept the information and to be simple operation, the final output. Asa branch of artificial intelligence,artificial neural network has been concerned by people of all walks of life, and has been applied to many fields since it was put forward. The RBF neural network is a feedforward neural network with single hidden layer deformation of the BP, The RBF neural network is the deformation of the BP network with a single hidden layer feedforward neural network, relatively simple structure, but also the speed of training and is applicable to nonlinear problems, is a kind of local approximation function, and his output results are generally linear. It may be local extreme, and the training time is longer in the local search. Therefore, this paper study the optimization of the RBF neural network, based on the FS920 fluorescence spectra of the platform.The main research contents are as follows:(1) Basedon The FS920 platform, made the choice of light source,monochromator, detectors, or others, and carried out experimental studies.(2) Analysis of the fluorescence of the substance, study the mechanism of the fluorescence and the chemical structure of the fluorescent substance, and the relationship between the fluorescence intensity and the concentration of the fluorescent substance.(3) The original data were processed by the method of Ensemble Empirical Mode Decomposition(EEMD), which is the basis of qualitative and quantitative analysis.(4) With the optimized ABC algorithm improved RBF neural network, as a new data prediction model of Ba P and BKF and sodium dodecyl benzene sulfonate,common washing powder for quantitative analysis.