Interpretation of fluorescence fingerprints of crude oils and other hydrocarbon mixtures using neural networks

摘要

An artificial intelligence system is used with a conglomeration of fluorescence data to provide a method of improving recognition of an unknown from its spectral pattern. Customized neural network systems allow the ultimate organization and resourceful use of assumption-free variables already existing in a total scanning fluorescence database for a much more comprehensive, discrete and accurate differentiation and matching of spectra than is possible with human memory. The invention provides increased speed of fingerprinting analysis, accuracy and reliability together with a decreased learning curve and heightened objectivity for the analysis.