6 results about "Partial least squares analysis" patented technology

Provided in the present disclosure are a fault prediction method and apparatus, a model determination method and apparatus, and a device and a storage medium. A fault prediction model determination method comprises: on the basis of a partial least squares analysis method and a historical fault result, performing feature extraction on acquired historical feature data; and determining a relationship function between input feature extraction data and a fault prediction result on the basis of historical feature extraction data, so as to determine a fault prediction model on the basis of the relationship function. In the fault prediction model determination method, a mapping relationship between feature extraction data and a fault prediction result can be more deeply extracted by means of a partial least squares analysis method, and then a relationship function is determined on the basis of the extracted mapping relationship, and a fault prediction model with a higher fault prediction accuracy is determined on the basis of the relationship function.

The invention relates to the field of liquor identification methods, in particular to a method for constructing a model for identifying authenticity of Maotai-flavor liquor, which is characterized by comprising the following steps of: 1, collecting carbon isotope data of a sample: measuring delta 13C values of ethanol and flavor skeleton components in the liquor sample, and generating a stable carbon isotope data set of the Maotai-flavor liquor; 2, analyzing and screening characteristic variables based on a partial least square method; 3, constructing a machine learning model: importing the screened feature variables into the machine learning model, and training the feature variables through the machine learning model; and 4, model application: based on the trained machine learning model, importing the characteristic variables of the to-be-detected wine sample into the model for identification, and obtaining an identification result of the to-be-detected wine sample. According to the method, the delta 13C values of the ethanol and the flavor skeleton components of the ethanol in the Maotai wine are measured based on the stable isotope mass spectrometry technology, the model is constructed, irrelevant noise is eliminated in combination with PLS-DA analysis, and the robustness, stability and accuracy of the whole model are improved.

The invention discloses a method for identifying tricholoma matsutake and similar edible mushrooms thereof. The method comprises the following steps: extracting lipid of tricholoma matsutake and similar edible mushrooms thereof; the method comprises the following steps: preparing a sample solution to be tested, analyzing and identifying a lipid molecular structure through ultra-high performance liquid chromatography-high resolution mass spectrometry, and constructing a standard curve through lipid standard substances of different lipid types, so as to realize quantitative analysis of lipid molecules in tricholoma matsutake and similar edible mushrooms. According to the method, qualitative and quantitative results of lipid analysis are synthesized, differential lipid molecules are screened out through least partial square method analysis and p value calculation, and the tricholoma matsutake and similar edible mushroom varieties are identified according to the differential lipid molecules or the differential lipid molecules and the content of the differential lipid molecules. According to the method, only a small amount of edible mushroom powder needs to be taken to extract lipid, the UPLC-HRMS technology is adopted, lipid molecular structure identification and accurate quantification are achieved, and by combining the analysis means of chemometrics, differential lipid can be screened out to be used for identifying tricholoma matsutake and similar edible mushroom varieties.

The invention relates to the technical field of chicken breast muscle variety identification. The invention provides a metabonomics-based method for identifying breast muscles of Hetian chicken and Zhouhole chicken, which comprises the following steps: (1) extracting a sample to be detected to obtain a metabolite extract, and collecting metabonomics data; (2) performing principal component analysis and orthogonal partial least square analysis on the metabonomics data, and screening out differential metabolites and potential characteristic markers; and (3) carrying out ultra-high performance liquid chromatography-mass spectrometry detection on a to-be-detected sample by using the screened potential characteristic markers, and identifying. According to the method, the variety identification of the breast muscles of the Hetian chicken and the Xianchang chicken can be efficiently and accurately completed by combining an ultra-high performance liquid chromatography-mass spectrometry technology with high-precision statistical analysis, and the method has a wide application prospect, especially in the aspects of food traceability, quality control and variety identification.

The invention discloses a peucedanum praeruptorum dunn medicinal material quality analysis method based on a near-infrared technology, and belongs to the field of medicinal material quality analysis methods. The method comprises the following steps: collecting near infrared spectrum data of a radix peucedani medicinal material sample; preprocessing the near infrared spectrum data, and modeling by adopting one algorithm of a random forest, a back propagation neural network and partial least square analysis to respectively obtain quantitative analysis models capable of measuring at least one effective component in the content of praeruptorin A, the content of praeruptorin B and the content of praeruptorin C; obtaining the content of effective components in the radix peucedani medicinal material sample based on the model, and analyzing the quality of the radix peucedani medicinal material. According to the present invention, the near infrared technology is combined with the chemometrics to achieve the rapid determination of the three active components such as the praeruptorin A, the praeruptorin B and the praeruptorin C in the peucedanum praeruptorum dunn medicinal material; the sample preparation process is convenient, the sample is lossless, no chemical reagent pollution risk exists, and the result is accurate.

The application discloses a method for identifying the genuineness of radix codonopsis based on an electronic tongue and GC-MS technology, and discloses the following technical scheme: the electronic tongue technology is used to evaluate the tastes of radix codonopsis (Lu Dang, Bai Tiao Dang, Tai Dang, Wen Dang, Dao Dang and Tiao Dang) solutions of different commodities, principal component analysis and partial least square analysis methods are used to analyze the electronic tongue data of the radix codonopsis of different commodities, and it is found that the radix codonopsis of different commodities can be well distinguished through the taste identification of the electronic tongue. Through the primary metabolomics difference research of Lu Dang and other commodity radix codonopsis by GC-MS, 35 metabolites are identified and recognized, and PCA analysis and orthogonal partial least square analysis are conducted on the results, and 17 differential metabolites in the radix codonopsis are found. The Lu Dang and Bai Tiao Dang and Tai Dang of the same origin are analyzed, and 5 differential metabolites are found. The application can provide an efficient and objective analysis method for identifying the genuineness of radix codonopsis medicinal materials.