Study on Rural Residents Income Growth Based on Quasi-Stepwise Regression Model

2013 ◽  
pp. 695-703
Author(s):  
Lingbo Cong ◽  
Jihua Cai
Keyword(s):  
Regression Model ◽  
Stepwise Regression ◽  
Income Growth ◽  
Rural Residents

scholarly journals Application of combined model of stepwise regression analysis and artificial neural network in data calibration of miniature air quality detector

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bing Liu ◽  
Qingbo Zhao ◽  
Yueqiang Jin ◽  
Jiayu Shen ◽  
Chaoyang Li
Keyword(s):  
Neural Network ◽  
Air Quality ◽  
Regression Model ◽  
Multilayer Perceptron ◽  
Stepwise Regression ◽  
Control Point ◽  
Measurement Data ◽  
Environmental Indicators ◽  
Air Pollutant ◽  
Mlp Model

AbstractIn this paper, six types of air pollutant concentrations are taken as the research object, and the data monitored by the micro air quality detector are calibrated by the national control point measurement data. We use correlation analysis to find out the main factors affecting air quality, and then build a stepwise regression model for six types of pollutants based on 8 months of data. Taking the stepwise regression fitting value and the data monitored by the miniature air quality detector as input variables, combined with the multilayer perceptron neural network, the SRA-MLP model was obtained to correct the pollutant data. We compared the stepwise regression model, the standard multilayer perceptron neural network and the SRA-MLP model by three indicators. Whether it is root mean square error, average absolute error or average relative error, SRA-MLP model is the best model. Using the SRA-MLP model to correct the data can increase the accuracy of the self-built point data by 42.5% to 86.5%. The SRA-MLP model has excellent prediction effects on both the training set and the test set, indicating that it has good generalization ability. This model plays a positive role in scientific arrangement and promotion of miniature air quality detectors. It can be applied not only to air quality monitoring, but also to the monitoring of other environmental indicators.

scholarly journals China’s Emerging Global Middle Class

2020 ◽  
pp. 75-108
Author(s):  
Björn Gustafsson ◽  
Terry Sicular ◽  
Xiuna Yang
Keyword(s):  
Middle Class ◽  
High Income ◽  
Income Country ◽  
Income Growth ◽  
High Income Country ◽  
Urban Residents ◽  
Rural Residents ◽  
Small Minority ◽  
Chip Data ◽  
Global Middle Class

This chapter examines China’s middle class by using CHIP data for 2002, 2007, and 2013. “Middle class” is defined as having income high enough not to be regarded as poor but not so high as to be regarded as rich if living in a high-income country. Based on this definition, China’s middle class was extremely small in 2002; grew but was still less than 10 percent of the population in 2007; and by 2013 had expanded to one-fifth of China’s population, roughly 250 million people. Further analysis shows that China’s middle class is largely urban, lives in the East, and has other distinctive characteristics. Simulations reveal that past growth of China’s middle class was due to across-the-board, shared income growth rather than a redistribution of income. As of 2020 China’s middle class should double in size, constituting a majority of urban residents but still a small minority of rural residents.

Research on Related Problems of PM2.5 in Air

2014 ◽  
Vol 644-650 ◽  
pp. 5319-5324
Author(s):  
Tian Jiu Leng
Keyword(s):  
Regression Analysis ◽  
Boundary Conditions ◽  
Regression Model ◽  
Multiple Regression ◽  
Stepwise Regression ◽  
Multiple Regression Model ◽  
Stepwise Regression Analysis ◽  
Spatial Evolution ◽  
Analysis Method ◽  
Relevant Factors

In this paper, the relevant factors of PM2.5 and the degree of correlation between them were analyzed.The multiple regression model was established using stepwise regression analysis method and the temporal spatial evolution of PM2.5 was obtained by setting the initial and boundary conditions.

scholarly journals Material selection of natural fibre using a stepwise regression model with error analysis

2019 ◽  
Vol 8 (3) ◽  
pp. 2865-2879 ◽  
Author(s):  
Muhammad Noryani ◽  
Salit Mohd Sapuan ◽  
Mohammad Taha Mastura ◽  
Mohd Yusoff Moh Zuhri ◽  
Edi Syams Zainudin
Keyword(s):  
Error Analysis ◽  
Regression Model ◽  
Stepwise Regression ◽  
Material Selection ◽  
Natural Fibre ◽  
Selection Of

scholarly journals Migration of Rural Residents to Urban Areas Drives Grassland Vegetation Increase in China’s Loess Plateau

2019 ◽  
Vol 11 (23) ◽  
pp. 6764 ◽  
Author(s):  
Wei ◽  
Zheng ◽  
Zhang ◽  
Fang ◽  
Zhou ◽  
...  
Keyword(s):  
Regression Model ◽  
Loess Plateau ◽  
Human Activities ◽  
Vegetation Dynamics ◽  
Urban Areas ◽  
Principal Component Regression ◽  
Principal Component ◽  
Grassland Vegetation ◽  
Rural Residents ◽  
Urbanization Rate

Human activities are critical factors influencing ecosystem sustainability. However, knowledge on regarding the mechanisms underlying the response of vegetation dynamics to human activities remains limited. To detect the driving factors and their individual contribution to the grassland vegetation dynamics in China’s Loess Plateau, a structural equation model (SEM) and a principal component regression model were built. The SEM showed that population change and urbanization, temperature and humidity, and agriculture and economy accounted for 62.5%, 31.2%, and 7.7%, respectively, of the overall impact directly affecting grassland vegetation dynamics. Furthermore, the principal component regression model demonstrated that the effects of the urbanization rate on the grassland above-ground biomass exceeded those of the other factors. The agriculture population had the maximum negative effect on grassland area. The higher the urbanization rate means the higher the number of residents migrates from rural to urban areas. Following this argument, the disturbances of human activities to grassland vegetation were expected to gradually decrease in rural areas, where the vast majority of the Loess Plateau is located. The migration of rural residents to urban areas promoted the increase in biomass and areas of grassland vegetation. Our findings suggest that the effect of urbanization should be considered when assessing vegetation change.

Personality Correlates of Locus of Control among College Women

1978 ◽  
Vol 43 (3_suppl) ◽  
pp. 1129-1130 ◽  
Author(s):  
Joseph C. Bledsoe ◽  
William C. Baber
Keyword(s):  
Locus Of Control ◽  
Regression Model ◽  
College Women ◽  
Stepwise Regression ◽  
Personality Factor ◽  
Ego Strength ◽  
Personality Correlates ◽  
Will Power

Personality correlates of locus of control were investigated for a group of 205 college women. Eight 16-Personality Factor variables were reliably correlated with scores on locus of control. Internal women were more likely to be controlled, emotionally stable, conscientious, trusting, shrewd, and sociable; external women were more likely to be excitable and insecure. A 6-variable stepwise regression model using will power, ego strength, sociability, trust, creativity, and shrewdness as variables gave a mutiple R of .442 and accounted for 20% of the variance.

The central vein sign in multiple sclerosis patients with vascular comorbidities

2020 ◽  
pp. 135245852094378 ◽  
Author(s):  
François Guisset ◽  
Valentina Lolli ◽  
Céline Bugli ◽  
Gaetano Perrotta ◽  
Julie Absil ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Regression Model ◽  
Stepwise Regression ◽  
Univariate Analysis ◽  
Lower Percentage ◽  
Central Vein ◽  
Perivascular Spaces ◽  
Median Frequency ◽  
Multiple Sclerosis Patients ◽  
The Impact

Background: The central vein sign (CVS) is an imaging biomarker able to differentiate multiple sclerosis (MS) from other conditions causing similar appearance lesions on magnetic resonance imaging (MRI), including cerebral small vessel disease (CSVD). However, the impact of vascular risk factors (VRFs) for CSVD on the percentage of CVS positive (CVS+) lesions in MS has never been evaluated. Objective: To investigate the association between different VRFs and the percentage of CVS+ lesions in MS. Methods: In 50 MS patients, 3T brain MRIs (including high-resolution 3-dimensional T2*-weighted images) were analyzed for the presence of the CVS and MRI markers of CSVD. A backward stepwise regression model was used to predict the combined predictive effect of VRF (i.e. age, hypertension, diabetes, obesity, ever-smoking, and hypercholesterolemia) and MRI markers of CSVD on the CVS. Results: The median frequency of CVS+ lesions was 71% (range: 35%–100%). In univariate analysis, age ( p < 0.0001), hypertension ( p < 0.001), diabetes ( p < 0.01), obesity ( p < 0.01), smoking ( p < 0.05), and the presence of enlarged-perivascular-spaces on MRI ( p < 0.005) were all associated with a lower percentage of CVS+ lesions. The stepwise regression model showed that age and arterial hypertension were both associated with the percentage of CVS+ lesions in MS (adjusted R2 = 0.46; p < 0.0001 and p = 0.01, respectively). Conclusion: The proportion of CVS+ lesions significantly decreases in older and hypertensive MS patients. Although this study was conducted in patients with an already established MS diagnosis, the diagnostic yield of the previously proposed 35% CVS proportion-based diagnostic threshold appears to be not affected. Overall these results suggest that the presence of VRF for CSVD should be taken into account during the CVS assessment.

Modeling of slag foaming height of electric arc furnace using stepwise regression analysis

2020 ◽  
Vol 117 (1) ◽  
pp. 114 ◽  
Author(s):  
Jaegak Lee ◽  
Jungkeuk Kim ◽  
Haejin Hwang ◽  
Kyungchan Son ◽  
Wonseok Jeon ◽  
...  
Keyword(s):  
Regression Model ◽  
Stepwise Regression ◽  
Correlation Coefficients ◽  
Electric Arc Furnace ◽  
Electric Arc ◽  
Sensor Data ◽  
Coefficient Of Determination ◽  
Arc Furnace ◽  
Oxygen Injection ◽  
Slag Foaming

Slag foaming directly affects the productivity and quality of steel during the electric arc furnace (EAF) process. Therefore, the slag foaming height needs to be monitored in real-time. However, direct measurement of the slag foaming height is difficult to achieve because the inside of the EAF consists of harsh environments, i.e., high temperature and the presence of gas and dust. A stepwise regression model of the slag foaming height was created using sensor data from the EAF. A total of 272 operational data sets from the EAF process were used to develop and validate the regression model. This data came from 140ton DC-EAF of Dongkuk Steel in Pohang, Korea. We randomly selected 80% of the data for developing the regression model; the remaining 20% of data were used for model validation. The model was validated using the validation benchmark coefficient of determination (R2) and correlation coefficients. As a result, the important variables of slag foaming were statistically selected a priori. Using the regression model, the slag foaming height can be predicted without additional sensors. Based on the developed model, the effects of oxygen injection and carbon injection on the slag foaming height of EAF were predicted and are discussed herein.

Does the Trade Union Promote the Employee Development in Tobacco Enterprise: Evidence from China

2021 ◽  
Vol 7 (6) ◽  
pp. 5717-5725
Author(s):  
Sun Chenghao ◽  
Zhang Yuxin ◽  
Sun Hanqiao
Keyword(s):  
Regression Model ◽  
Trade Union ◽  
Trade Unions ◽  
Stepwise Regression ◽  
Employee Development ◽  
Mediating Effect ◽  
Self Development ◽  
The Relationship

Objectives: Based on the data of questionnaire collected from tobacco enterprise, this paper uses regression model to focus on the relationship between the trade unions and the employee development. Besides, causal stepwise regression is adopted to find out the influential mechanism. The results show that the trade union in tobacco enterprise can significantly promote employee development by the mediating effect of contract guarantee, and this effect is more obvious in female groups. It is important to strengthen the development of trade union, creating more self-development opportunities for employees in tobacco enterprise.

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