Papers by Keyword: Partial Least Squares

Abstract: Polymers are commonly used in concrete materials. The type and concentration of polymer are important information for stakeholders, because they have a critical impact on the properties of concrete materials. Therefore, reliable and accurate information is highly desirable. To this end, Fourier Transform Infrared Spectroscopy (FTIR) and Thermogravimetric Analysis (TGA) are used to analyze polymer contents in construction materials. FTIR spectroscopy is a suitable technique to identify the polymer type using IR spectrum matching. Additionally, functional group information can be easily obtained from each peak. Attenuated Total Reflection (ATR) method can be used to measure extracted polymers from construction materials to obtain IR spectra, and match against the library database to identify the polymer materials. TGA is one of the common thermal analysis methods. It measures the weight loss or gain of sample due to chemical reactions such as vaporization, decomposition and oxidation as a function of temperature. In this paper, we will discuss development of reliable analytical methods with which mixtures of polymer, fine aggregate and cement with different percentages of polymer content were prepared and evaluated.

Abstract: Study traditional Chinese medicine prescription compatibility chemical components Dose-response relationship based on multiplicative signal correction and partial least squares (MSC-PLS). Method: mathematical modeling base on MSC-PLS. Results: study the compatibility chemical components of the dachengqi decoction; mining the regression coefficient and equation, VIP sorting, loadings Bi plot base on the method. Conclusion: the method mining the data information and optimization the compatibility of the dachengqi decoction cure ileus rats is feasible and effective.

Abstract: Data mining and optimize traditional Chinese medicine (TCM) prescription compatibility based on wavelet denoise spectral and partial least squares (WDS-PLS). Method: First of all, experimental design: with reference to the original formula, the herbal medicines in a prescription designed nine formula based on mixing uniform design; Secondly, obtain experimental data and data standardization; Finally, mathematical modeling, data mining and optimize TCM prescription compatibility base on WDS-PLS.Results: gain the regression coefficient and equation, VIP sorting, loadings Bi plot, and seek out the optimized direction of the prescription. Conclusion: the method data mining and optimize the compatibility of the dachengqi decoction is feasible and effective.

Abstract: Study traditional Chinese medicine prescription compatibility based on multiplicative signal correction and partial least squares (MSC-PLS). Method: mathematical modeling base on MSC-PLS. Results: gain the regression coefficient and equation, VIP sorting, loadings Bi plot, and seek out the optimized direction of the prescription.Conclusion: using multiplicative signal correction and partial least squares method optimize the compatibility of the dachengqi decoction cure ileus rats is feasible and effective.

Abstract: An aerodynamic modeling method based on WNN with Partial Least Squares (PLS) is proposed. In the method, PLS first is applied to extract the feature of original aerodynamic data samples, and then the obtained feature is used to establish the WNN aerodynamic model for aircraft stall from flight test data. Simulation results are given to illustrate that the proposed method is effective and feasible.

Abstract: Three methods, selecting characteristic lines of elements contained in the samples manually, selecting intensive spectral partitions manually and the whole spectra, were used to reduce dimensions of spectra of 27 steel samples acquired by Laser-Induced Breakdown Spectroscopy. The PLS models were built based on the data after dimension reduction to quantify the Mn concentration of samples. The results show that, PLS model built based on selecting intensive spectral partitions can achieve the best result with the least complexity and the highest generalization ability. Selecting intensive partitions is a promising solution to reduce dimensions for original spectra.

Abstract: In order to identify the content of Ganoderma lucidum powder in Ganoderma lucidum spore powder, diffuse reflectance spectroscopy of samples were collected by the Fourier near-infrared spectrometer. The spectroscopy was pretreated by minimum and maximum normalization and then analyzed with partial least squares (PLS) method. The spectral at 6110 cm^-1 to 4598 cm^-1 was establish PLS model with factors number 10. The result show that the squared correlation coefficient R² between predicted value and true value is 99.99%, and RMSECV is 0.382. In conclusion, Ganoderma lucidum spore powder and Ganoderma lucidum powder can be identified accurately and quickly based on near-infrared spectroscopy and PLS.

Abstract: Experimental data for the human body PET multi-variable, non-linear distribution and other characteristics, the use of fusion partial least squares support vector machine variables effectively extracted from the principal component, reducing the number of variables and the exclusion of noise information to construct a linear regression with the dependent variables model, fitting the model has good accuracy and generalization for PET clinical trials provide effective technical support and research ideas.

Abstract: Modeling concrete compressive strength is useful to ensure quality of civil engineering. This paper aims to compare several Extreme learning machines (ELMs) based modeling approaches for predicting the concrete compressive strength. Normal ELM algorithm, Partial least square-based extreme learning machines (PLS-ELMs) algorithm and Kernel ELM (KELM) algorithm are used and evaluated. Results indicate that the normal ELMs algorithm has the highest modeling speed, and the KELM has the best prediction accuracy. Every method is validated for modeling concrete compressive strength. The appropriate modeling approach should be selected according different purposes.

Abstract: Processing of following holes may decrease manufacture precision of processed spindle holes. To decrease the unfavorable influence on spindle holes and improve the manufacture reliability of spindle boxes, the paper applies a partial correlation relationship and hypothesis testing to find the holes which have correlation with the spindle hole. The partial least squares establishes the mathematical model of manufacture error correlativity so that the paper finds the magnitude of influence these holes has on the spindle hole through coefficients of the modeling. The model provides the foundation for improving manufacturing accuracy of holes that have great influence on spindle holes to decrease manufacturing error of the spindle hole and improve the reliability of spindle boxes. The example proves the methods applied to decrease the unfavorable influence on the spindle hole are specific and operable.