Chinese liquors with different years have become the focus of the enterprise development as the high-end products in the industry. But the standards about the years of the product have a greater randomness. Therefore, to establish a technical standard of liquor’s year has become desperately needed in order to regulate the industry and the market. Based on three-dimensional fluorescence spectra of the original degree Chinese liquors with different years, which belongs to a well-known series in China, this article establishes a year forecast model of Chinese liquors. The research contents and innovations are as follows: firstly, from the analysis of correlation between the fluorescence spectra and the liquor’s year, it is found that the correlation coefficient of three-dimensional fluorescence spectra between 0.5 year and others reaches to 0.811 4. The year information in the original spectra are mainly distributed in the area of the excitation wavelength of 200~230 and 250~320 nm and the emission wavelength in the band of 400~500 nm. The year information of the derivative spectrum distributes widely and its dispersion is high, in which the two order derivative spectra of the year information distribute more discrete. Secondly, the correlations of the two-dimensional fluorescence spectra with the excitation wavelength of 300 nm is studied. The results show that there is a high multicollinearity in the original fluorescence spectra. The value of the correlation coefficient is close to 1, in the whole range of the emission wavelength of 400~600 nm. The resolution capability can be improved after derivation, and the multicollinearityalso can be reduced at this time. Two order derivative has a better effect on the suppression of multicolinearity while most of the correlation coefficient are less than 0.6. Finally, the year forecast model of the Chinese liquors is established with the excitation wavelength of 300 nm using quantum genetic algorithm and wavelet neural network. The concept of spectral modeling information density is proposed. It is found that the error of the root mean square of original spectra in the prediction reaches to 5.4 years. The modeling effect is the worst. The main reason for this is that the original spectrum has a serious of multicollinearity, which leads to the correlation between the spectra and the year are not significant and the changes are slowly. The derivation spectra have a higher information density and a better effect of modeling than the original spectra. The validation set correlation coefficient of the second derivative spectra can reach to 0.999 8, and the error of the year forecast is 0.79 years. The research results provide not only a convenient optical method for the year calibration of the liquor, but also an important reference for the fluorescence spectra research of the multi-component gradient system.