Fluorescence optical fiber measurement system based on an advanced Neural Network (NN) ensemble algorithm

Noisy Spread based Ensemble Neural Networks is a new neural network ensemble algorithm with high integration, anti-interference and high precision. In this paper, it's applied to fluorescence spectra of the oil in water (classification and identification). The method uses optical spectroscopy to measure excitation fluorescence spectroscopy in the pool of crude oil and mineral oil in the range 230 ∼ 400nm, belong to UV spectral region: spectral interval of 5nm, recording fluorescence spectroscopy data, then the integration neural networks were established by the enhanced T individual neural networks. Vote method for the classification of fluorescence spectra characteristics and the average method for nonlinear regression. Experiments show that the neural network integrated for fluorescence spectral measurement system of oil in water identification and processing higher accuracy.