scholarly journals External Deformation Monitoring and Improved Partial Least Squares Data Analysis Methods of High Core Rock-Fill Dam (HCRFD)

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 444
Author(s):  
Xiang Cheng ◽  
Qingquan Li ◽  
Wei Zhou ◽  
Zhiwei Zhou
Keyword(s):  
Data Analysis ◽  
Least Squares ◽  
Water Level ◽  
Partial Least Squares ◽  
Small Angle ◽  
Traditional Method ◽  
Water Storage ◽  
Deformation Monitoring ◽  
Independent Variables ◽  
Rock Fill

External deformation monitoring of high core rock-fill dams (HCRFDs) is an important and difficult part of safety monitoring. The traditional method of external deformation monitoring and data analysis for HCRFDs is to use a total station for small angle observations and establish a regression model to analyze the results. However, the small angle method has low accuracy and a low automation degree, and there is multicollinearity between the independent variables, which affects the parameter estimation and leads to the failure of model establishment. The angle forward intersection method is adopted in this paper for observation, and an improved partial least squares method (IPLS) is proposed to eliminate the multicollinearity of the independent variables. Compared to the traditional method, the improved observation method exhibits high accuracy and a high automation degree. The new data analysis method can not only eliminate multicollinearity but also improve the interpretation ability of the model. The data from the initial stage of water storage shows that the displacement increases with the increase in the upstream water level and time, and the speed of water storage is proportional to the displacement. The water level and time are the main influencing factors. This conclusion provides a theoretical basis for reservoir management departments to control water levels and gate opening and closing. The method in this paper can be applied to arch dams, gravity dams, and other types of waterpower engineering systems.

Combining the advantages of multilevel and orthogonal partial least squares data analysis for longitudinal metabolomics: Application to kidney transplantation

2020 ◽  
Vol 1099 ◽  
pp. 26-38 ◽  
Author(s):  
Yoric Gagnebin ◽  
Julian Pezzatti ◽  
Pierre Lescuyer ◽  
Julien Boccard ◽  
Belen Ponte ◽  
...  
Keyword(s):  
Kidney Transplantation ◽  
Data Analysis ◽  
Least Squares ◽  
Partial Least Squares

Characterization of the Thermal Degradation of Vinegar and the Construction of an Identification Model for Chinese Geographical Indication Vinegars by the Py-GC-MS Technique

2017 ◽  
Vol 100 (2) ◽  
pp. 503-509 ◽  
Author(s):  
Cen Xiong ◽  
Zhiyi Su ◽  
Yanjie Zhezng ◽  
Qi Wang ◽  
Yejing Ling ◽  
...  
Keyword(s):  
Data Analysis ◽  
Thermal Degradation ◽  
Least Squares ◽  
Partial Least Squares ◽  
Modeling Method ◽  
Geographical Indication ◽  
Time To Build ◽  
Pls Modeling ◽  
Identification Model

Abstract The pyrolysis (Py)-GC-MS technique was first introduced for the identification of two kinds of Chinese geographical indication vinegars because its advantages are that it is a simple and convenient sample pretreatmentand inlet method. Abundant Py information about vinegars was obtained using Py-GC-MS; 21 common peaks were selected. With the help of the classical partial least-squares (PLS) modeling method for data analysis, two identification models for Shanxi extra-aged (SX) and Zhenjiang (ZJ) vinegars were established, respectively. An N-reducing method was used to select the variables. The variables were reduced one at a time to build the PLS models with the lowest number of misjudgments. Both models had good recognition rates, identifying over 90% of samples correctly. Thus, combining Py-GC-MS and PLS could be regarded as an effective method for the identification of SX and ZJ vinegars.

scholarly journals Effect of SME Food Entrepreneurs Knowledge on Halal Certification for Certified Awareness Using Partial Least Square

2019 ◽  
Vol 20 (2) ◽  
pp. 36
Author(s):  
Ida Giyanti ◽  
Erna Indriastiningsih
Keyword(s):  
Data Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Structural Equation Model ◽  
Structural Equation ◽  
Equation Model ◽  
The Other ◽  
Medium Enterprise ◽  
The Impact ◽  
Comprehension Rate

This study aims to predict the impact of the understanding of halal certification by Small Medium Enterprise (SME) entrepreneurs on the intention to conduct halal certification. This study was conducted in the Cooperative and SME Office of Surakarta City. The Halal Certification Comprehension Rate was assessed using three variables.   We had knowledge of halal (PGT), perceived halal certification advantages (MNF), and perceived halal certification procedures (PROS).  Structural Equation Model-Partial Least Squares (SEM-PLS) was used for data analysis.  The results show that SMEs have a good knowledge of halal and agree that halal certification is beneficial to their businesses.  We found, though, that the processes for handling Halal Certification are relatively complex. Based on the study, the perception of Halal Certification Benefits (MNF) is significantly affected by the intention of SMEs to conduct Halal Certification (NHL). The other two results show a positive correlation. However, they are not statistically significant.This study aims to predict the impact of the understanding of halal certification by Small Medium Enterprise (SME) entrepreneurs on the intention to conduct halal certification. This study was conducted in the Cooperative and SME Office of Surakarta City. The Halal Certification Comprehension Rate was assessed using three variables.   We had knowledge of halal (PGT), perceived halal certification advantages (MNF), and perceived halal certification procedures (PROS).  Structural Equation Model-Partial Least Squares (SEM-PLS) was used for data analysis.  The results show that SMEs have a good knowledge of halal and agree that halal certification is beneficial to their businesses.  We found, though, that the processes for handling Halal Certification are relatively complex. Based on the study, the perception of Halal Certification Benefits (MNF) is significantly affected by the intention of SMEs to conduct Halal Certification (NHL). The other two results show a positive correlation, but they are not statistically significant.

scholarly journals PLS-SEM STATISTICAL PROGRAMS: A REVIEW

2021 ◽  
Vol 5 (1) ◽  
pp. i-xiv
Author(s):  
Mumtaz Ali Memon ◽  
T. Ramayah ◽  
Jun-Hwa Cheah ◽  
Hiram Ting ◽  
Francis Chuah ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Data Analysis ◽  
Least Squares ◽  
Partial Least Squares ◽  
Multivariate Data Analysis ◽  
Structural Equation ◽  
Multivariate Data ◽  
Informed Decision ◽  
Equation Modeling

Partial least squares structural equation modeling (PLS-SEM) is one of the most widely used methods of multivariate data analysis. Although previous research has discussed different aspects of PLS-SEM, little is done to explain the attributes of the different PLS-SEM statistical applications. The objective of this editorial is to discuss a variety of PLS-SEM applications, including SmartPLS, WarpPLS, and ADANCO. It is written based on information received from the developers via emails as well as our ongoing understanding and experience of using these applications. We hope this editorial can serve as a manual for users to understand the unique characteristics of each PLS-SEM application and make an informed decision on the most appropriate application in their research.

[MEG]PLS: A pipeline for MEG data analysis and partial least squares statistics

NeuroImage ◽  
2016 ◽  
Vol 124 ◽  
pp. 181-193 ◽  
Author(s):  
Michael J. Cheung ◽  
Natasa Kovačević ◽  
Zainab Fatima ◽  
Bratislav Mišić ◽  
Anthony R. McIntosh
Keyword(s):  
Data Analysis ◽  
Least Squares ◽  
Partial Least Squares
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