The partial least-squares regression analysis of impact factors of coordinate measuring machine dynamic error

2008 ◽  
Author(s):  
Mei Zhang ◽  
Yetai Fei ◽  
Li Sheng ◽  
Xiushui Ma ◽  
Hong-tao Yang
2013 ◽  
Vol 827 ◽  
pp. 428-434 ◽  
Author(s):  
Zhi Jian Liu ◽  
Zhi Hua Yang ◽  
Rong Chen ◽  
Shu Ming Zhou

Aiming at monthly load of power system, it is forecasted by using the method of partial least squares regression and the model of improving grey prediction.First, using improved grey prediction model to forecast impact factors,then establishing partial least squares model according to the characteristics of the monthly load and the change of the main impact factors. The final fitted out a linear relation between load and impact factors. Practical example shows that the method has higher prediction accuracy, effectiveandfeasible.


2004 ◽  
Vol 87 (5) ◽  
pp. 1164-1172 ◽  
Author(s):  
Manuela Buchgraber ◽  
Franz Ulberth ◽  
Elke Anklam ◽  
H Bernaert ◽  
B Cleenewerck ◽  
...  

Abstract A European interlaboratory study was conducted to validate an analytical procedure for the detection and quantification of cocoa butter equivalents in cocoa butter and plain chocolate. In principle, the fat obtained from plain chocolate according to the Soxhlet principle is separated by high-resolution capillary gas chromatography into triacylglycerol fractions according to their acyl-C-numbers, and within a given number, also according to unsaturation. The presence of cocoa butter equivalents is detected by linear regression analysis applied to the relative proportions of the 3 main triacylglycerol fractions of the fat analyzed. The amount of the cocoa butter equivalent admixture is estimated by partial least-squares regression analysis applied to the relative proportions of the 5 main triacylglycerols. Cocoa butter equivalent admixtures were detected down to a level of 2% related to the fat phase, corresponding to 0.6% in chocolate (assumed fat content of chocolate, 30%), without false-positive or -negative results. By using a quantification model based on partial least-squares regression analysis, the predicted cocoa butter equivalent amounts were in close agreement with the actual values. The applied model performed well at the level of the statutory limit of 5% cocoa butter equivalent addition to chocolate with a prediction error of 0.6%, assuming a chocolate fat content of 30%.


2014 ◽  
Vol 39 (5) ◽  
pp. 463-465
Author(s):  
Kai CAI ◽  
Zhang-min XIANG ◽  
Shu-ping ZHOU ◽  
Zhao-liang GENG ◽  
Yong-hui GE ◽  
...  

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