Analysis Of Model Of Complex Environmental And Biological Sample

The rapid development of technology has led to the progress of society.A lot of data can be obtained in a short time.Data contain rules.Stoichiometry provides a possibility for discovering rules.Pattern recognition technology is developing faster,which is a good way to discover rules.Pattern recognition technology is widely applied in many fields,such as biology,energy,economy,chemistry and so on.Through computer and mathematics to find the rules of complex data.Aiming at the problems of analysis in the complex environmental and biological samples,using qualitative and quantitative analysis methods and other auxiliary methods to solve the auxiliary methods.Quantitative methods are reviewed,such as multiple linear regression,principal component analysis,partial least squares,artificial neural network,support vector machines and other methods.Different complex systems with the application of existing or new models,the specific research contents are as follows:1.On the basis of data about different drugs measured by X ray diffraction(XRD),using principal component analysis(PCA)method to analyze the data of XRD.The results showed that the classification effect of different drugs was better by PCA.2.Using a variety of trace elements content in serum of patients with lung cancer,using ROC curve of statistical analysis method and independent sample T test to analyst the data.3.Using the knowledge of chemometrics and combined with Raman spectrum technique and several preprocessing methods.The serum tumor feature information was been extracted.Through principal component analysis(PCA),non negative matrix analysis(NMF),partial least squares discriminate analysis(PLS-DA),nonlinear discriminate analysis(ULDA),linear discriminate analysis(LDA)for judgment and identification of patients with normal and cancer to explore the early screening of cancer.