A method for data processing and optimisation of a neural network for application in the determination of physical property data of hydrocarbon products from measured (Near) I.R. spectral absorbances, characterized by the steps of: a) measuring the I.R. spectra of a large set of hydrocarbon product samples from a wide range of sources; b) selecting a harmonic region; c) converting a number of the said wavelengths to absorption data and using said absorption data as an input to a neural network; d) training the neural network to correlate the absorbance values with said relevant physical property; e) generating a set of values of the interconnection weights and biases of the network; and f) applying these adjusted values, utilizing the neural network algorithm to (near-)infrared spectra. |