A nonlinear regression analysis method based on Stakeholder Theory Model for performance evaluation of poverty reduction of agricultural operators

2019 ◽  
pp. 002072091989420
Author(s):  
Zhenmin Wang
Keyword(s):  
Regression Analysis ◽  
Performance Evaluation ◽  
Stakeholder Theory ◽  
Nonlinear Regression ◽  
Poverty Reduction ◽  
Least Squares Method ◽  
Theory Model ◽  
Analysis Method ◽  
Nonlinear Regression Analysis ◽  
Policy Supply

A nonlinear regression analysis method for performance evaluation of poverty reduction of agricultural operators based on Stakeholder Theory Model analysis was proposed to improve the effectiveness of performance evaluation of poverty reduction of a new type agricultural operator in poverty-stricken areas. Firstly, it can find out which interest demands of different stakeholders and which interest realization paths have significant impact on the task performance and peripheral performance of the policy supply of new agricultural operators through factor analysis and regression analysis of the questionnaire data of stakeholders to provide sufficient basis for the appropriate revision and adjustment of policy supply; secondly, the nonlinear regression model is established by using the nonlinear least squares method to fit, control, and forecast the performance evaluation of poverty reduction behavior of agricultural operators, which is more accurate than linear regression in both object and method. Finally, the effectiveness of the proposed algorithm is verified by empirical analysis.

scholarly journals Analyzing Loose Contact Oxidation of Diesel Engine Soot and Ag/CeO2 Catalyst Using Nonlinear Regression Analysis

2017 ◽  
Vol 12 (1) ◽  
pp. 14 ◽  
Author(s):  
Yasukazu Kobayashi ◽  
Riki Hikosaka
Keyword(s):  
Regression Analysis ◽  
Catalytic Activity ◽  
Diesel Engine ◽  
Nonlinear Regression ◽  
Physical Contact ◽  
Analysis Method ◽  
Nonlinear Regression Analysis ◽  
Contact Oxidation ◽  
Kinetics Of ◽  
Catalyzed Oxidation

<p>Loose contact (LC) oxidation kinetics of carbon black (CB) model soot and Ag/CeO<sub>2</sub> catalyst was deduced from thermogravimetric analysis (TG) experiments. In the LC mode at ≧750 K, CB particles were likely to be combusted also by non-catalyzed oxidation, especially those particles located far from the catalyst surface, as well as Ag/CeO<sub>2</sub>-catalyed oxidation. Since the non-catalyzed oxidation is not due to catalytic activity, in order to deduce the catalytic activity from TG data, a nonlinear regression analysis method was proposed in this study to extract only the catalyzed oxidation part of the TG data. It was verified that this was successfully done with the equations used by the very good curve fits to the experimental TG data, and the catalytic activity was correctly obtained from LC samples with various degrees of physical contact between the CB and catalyst. Copyright © 2016 BCREC GROUP. All rights reserved</p><p><em>Received: 18th July 2016; Revised: 12nd September 2016; Accepted: 20th September 2016</em></p><p><strong>How to Cite</strong>: Kobayashi, Y., Hikosaka, R. (2017). Analyzing Loose Contact Oxidation of Diesel Engine Soot and Ag/CeO<sub>2</sub> Catalyst Using Nonlinear Regression Analysis.<em> Bulletin of Chemical Reaction Engineering &amp; Catalysis</em>, 12 (1): 14-23 (doi:10.9767/bcrec.12.1.606.14-23)</p><p><strong>Permalink/DOI:</strong> http://dx.doi.org/10.9767/bcrec.12.1.606.14-23</p><p> </p>

The Real-Time Strain Monitoring of Tunnel Supporting Structure and Nonlinear Regression Analysis

2013 ◽  
Vol 718-720 ◽  
pp. 837-841 ◽  
Author(s):  
Bi He ◽  
Bin Wang ◽  
Chuan Li ◽  
Tong Yao Yang ◽  
Zhou Chun Cai ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Real Time ◽  
Nonlinear Regression ◽  
Measurement Data ◽  
Surrounding Rock ◽  
Analysis Method ◽  
Nonlinear Regression Analysis ◽  
Monitoring Point ◽  
The Real ◽  
Supporting Structure

Concrete embedded fiber Bragg grating strain sensors are used to monitor real-time strain of each section in the tunnel surrounding rock supporting structure, and the nonlinear regression analysis method is adopted to analysis the real-time measurement data. By using nonlinear regression analysis method, the strain development status of surrounding rock supporting structure can be grasped timely and the variation trend of the strain value of monitoring point can be predicted, which can provides foundations for judging the stability of tunnel supporting structure.

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