The present invention relates to a spectrum chemometric
analysis method based on segmented intelligent optimization. The present invention uses all sample spectra and
test analysis data and intelligently optimizes conditions to establish a main model. After the samples used for modeling are sorted according to
physical property data, they are divided into several sections according to the characteristics of
property distribution. Each section uses an intelligent
algorithm to optimize the best spectrum
pretreatment method and the spectrum area used for modeling, so as to respectively establish a sub-model of the index in each section, thereby improving the accuracy of the analysis result. In addition, after the samples are sorted according to the
physical property data, according to the characteristics of
property distribution, samples with similar types or structures and similar properties are classified into one category, and the sample spectra and data within the section are intelligently optimized for the
pretreatment method, modeling area and other conditions to establish a corresponding segmented model; after segmenting according to the characteristics of
property distribution, samples with similar types or structures can be classified into one category, and a separate sub-model can be established after the intelligent optimization conditions, which can effectively solve the problem that the accuracy of the analysis model is not high when the
physical property variation range of the existing quick evaluation
analysis method is large.