In this paper we firstly select main factors relating to urbanization level of Xiantao District in Hubei Province by main element, then, make model of urbanization level by analysis of multiple liner regression, and l...In this paper we firstly select main factors relating to urbanization level of Xiantao District in Hubei Province by main element, then, make model of urbanization level by analysis of multiple liner regression, and lastly predict its urbanization level展开更多
In oil and gas exploration,elucidating the complex interdependencies among geological variables is paramount.Our study introduces the application of sophisticated regression analysis method at the forefront,aiming not...In oil and gas exploration,elucidating the complex interdependencies among geological variables is paramount.Our study introduces the application of sophisticated regression analysis method at the forefront,aiming not just at predicting geophysical logging curve values but also innovatively mitigate hydrocarbon depletion observed in geochemical logging.Through a rigorous assessment,we explore the efficacy of eight regression models,bifurcated into linear and nonlinear groups,to accommodate the multifaceted nature of geological datasets.Our linear model suite encompasses the Standard Equation,Ridge Regression,Least Absolute Shrinkage and Selection Operator,and Elastic Net,each presenting distinct advantages.The Standard Equation serves as a foundational benchmark,whereas Ridge Regression implements penalty terms to counteract overfitting,thus bolstering model robustness in the presence of multicollinearity.The Least Absolute Shrinkage and Selection Operator for variable selection functions to streamline models,enhancing their interpretability,while Elastic Net amalgamates the merits of Ridge Regression and Least Absolute Shrinkage and Selection Operator,offering a harmonized solution to model complexity and comprehensibility.On the nonlinear front,Gradient Descent,Kernel Ridge Regression,Support Vector Regression,and Piecewise Function-Fitting methods introduce innovative approaches.Gradient Descent assures computational efficiency in optimizing solutions,Kernel Ridge Regression leverages the kernel trick to navigate nonlinear patterns,and Support Vector Regression is proficient in forecasting extremities,pivotal for exploration risk assessment.The Piecewise Function-Fitting approach,tailored for geological data,facilitates adaptable modeling of variable interrelations,accommodating abrupt data trend shifts.Our analysis identifies Ridge Regression,particularly when augmented by Piecewise Function-Fitting,as superior in recouping hydrocarbon losses,and underscoring its utility in resource quantification refinement.Meanwhile,Kernel Ridge Regression emerges as a noteworthy strategy in ameliorating porosity-logging curve prediction for well A,evidencing its aptness for intricate geological structures.This research attests to the scientific ascendancy and broad-spectrum relevance of these regression techniques over conventional methods while heralding new horizons for their deployment in the oil and gas sector.The insights garnered from these advanced modeling strategies are set to transform geological and engineering practices in hydrocarbon prediction,evaluation,and recovery.展开更多
In recent years,the real estate industry has achieved significant progress,driving the development of related sectors and playing a crucial role in economic growth.However,rapid real estate market expansion has led to...In recent years,the real estate industry has achieved significant progress,driving the development of related sectors and playing a crucial role in economic growth.However,rapid real estate market expansion has led to challenges,particularly concerning housing prices,which have drawn widespread societal attention.This article explores the theories of housing prices,analyzes factors influencing them,and conducts an empirical investigation of the impact of representative factors on ordinary residential prices.Using regression analysis and the entropy weight method,a mathematical model was developed to examine how various factors affect housing prices.展开更多
A common current source, generally used to bias cross-coupled differential amplifiers in a transconductor, controls third harmonic distortion (HD3) poorly. Separate current sources are shown to provide better control ...A common current source, generally used to bias cross-coupled differential amplifiers in a transconductor, controls third harmonic distortion (HD3) poorly. Separate current sources are shown to provide better control on HD3) . In this paper, a detailed design and analysis is presented for a transconductor made using this biasing technique. The transconductor, in addition, is made to offer high Gm, low power dissipation and is designed for linearly tunable Gm with current mode load as one of the applications. The circuit exhibits HD3) of less than –43.7 dB, high current efficiency of 1.18 V-1 and Gm of 390 μS at 1 VGp-p @ 50 MHz. UMC 0.18 μm CMOS process technology is used for simulation at supply voltage of 1.8 V.展开更多
As an extension of linear regression in functional data analysis, functional linear regression has been studied by many researchers and applied in various fields. However, in many cases, data is collected sequentially...As an extension of linear regression in functional data analysis, functional linear regression has been studied by many researchers and applied in various fields. However, in many cases, data is collected sequentially over time, for example the financial series, so it is necessary to consider the autocorrelated structure of errors in functional regression background. To this end, this paper considers a multiple functional linear model with autoregressive errors. Based on the functional principal component analysis, we apply the least square procedure to estimate the functional coefficients and autoregression coefficients. Under some regular conditions, we establish the asymptotic properties of the proposed estimators. A simulation study is conducted to investigate the finite sample performance of our estimators. A real example on China's weather data is applied to illustrate the validity of our model.展开更多
Five statistical methods including simple correlation, multiple linear regression, stepwise regression, principal components, and path analysis were used to explore the relationship between leaf water use efficiency ...Five statistical methods including simple correlation, multiple linear regression, stepwise regression, principal components, and path analysis were used to explore the relationship between leaf water use efficiency （WUE） and physiological traits （photosynthesis rate, stomatal conductance, transpiration rate, intercellular CO2 concentration, etc.） of 29 wheat cultivars. The results showed that photosynthesis rate, stomatal conductance, and transpiration rate were the most important leaf WUE parameters under drought condition. Based on the results of statistical analyses, principal component analysis could be the most suitable method to ascertain the relationship between leaf WUE and relative physiological traits. It is reasonable to assume that high leaf WUE wheat could be obtained by selecting breeding materials with high photosynthesis rate, low transpiration rate, and stomatal conductance under dry area.展开更多
Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of tre...Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.展开更多
Objective: To analyze the characteristics and possible mechanism of lipid metabolism in pregnant rats with intestinal flora imbalance. Methods: A total of 129 sexually mature female SD rats were divided into three gro...Objective: To analyze the characteristics and possible mechanism of lipid metabolism in pregnant rats with intestinal flora imbalance. Methods: A total of 129 sexually mature female SD rats were divided into three groups: non-pregnant group (untreated healthy rats), healthy pregnant group (natural insemination pregnant rats), and pregnant microflora disorder group (pregnant rats were given mixed antibiotics by gavage to build the modeling), with 43 rats in each group. The contents of TG, LDL, HDL and TC were detected by automatic biochemical analyzer, and the contents of SCD1, PGC-1 alpha, PEPCK, ApoE and MTTP genes were detected by fluorescence quantitative PCR technology. Regression analysis was used to explore the comprehensive influence of each gene on total cholesterol expression in rats. Principal component analysis was used to explore the internal mechanism of lipid metabolism in pregnant rats with intestinal flora disorder. Results: The contents of TG, TC, LDL and HDL were compared among the three groups of rats and the differences were statistically significant (P<0.05) . The expression levels of related genes (SCD1, PGC-1, PEPCK, ApoE, MTTP) in the three groups were statistically significant (P<0.05) . SCD1 content in the non-pregnant group, healthy pregnancy group, and disordered pregnancy group was (0.92±0.12) μg/mL, (1.20±0.15)μg/mL, and (1.53±0.20) μg/mL, respectively. PGC-1 alpha content in the non-pregnant group, healthy pregnancy group, and disordered pregnancy group was (1.34±0.21) μg/mL, (0.93±0.12) micron /mL, and (0.41±0.08) μg/mL, respectively. PEPCK content in the non-pregnant group, healthy pregnancy group, and disordered pregnancy group was (0.48±0.06) μg/mL, (0.35±0.09)μg/mL, and (0.22±0.05) μg/mL, and the differences were statistically significant (P<0.05) . Multivariate linear regression analysis showed that the influence of gene content on The effect of each gene content on TC content was in order from large to small: SCD1 (OR=4.572) , PGC-1 (OR=3.387) , PEPCK (OR=3.935) , ApoE (OR=3.597) , MTTP (OR=3.096) . The principal component analysis showed that three principal components could be extracted from five related genes of lipid metabolism in pregnant rats with intestinal dysbiosis: SCD1/PEPCK pathway (contribution rate: 36.28%) , PGC-1 /ApoE pathway (contribution rate: 30.42%) , and MTTP pathway (contribution rate: 15.37%) . Conclusion: After pregnancy, blood lipids in rats are significantly increased while the imbalance of intestinal flora will lead to decreased blood lipids. The disorder of lipid metabolism in pregnant rats with intestinal flora imbalance is mainly related to the disorder of gene expression, which further affects the functions of SCD1/PEPCK, PGC-1 /ApoE and MTTP pathways.展开更多
In this article,it discusses the di£ferences in economic development between urban and rural areas and regions in our country from the perspective of education investment and fixed asset investment.Based on the p...In this article,it discusses the di£ferences in economic development between urban and rural areas and regions in our country from the perspective of education investment and fixed asset investment.Based on the provincial data of 31 provinces from 1999 to 2017 released by National Bureau of Statistics,it expends the Cobb-Douglas model and Lucas model,and analyses the data with multiple linear regression models.From the study,it finds that compared with investment in fixed assets,investment in education has a larger role in promoting economic development,which is more obvious in the underdeveloped central and western regions and rural areas.However,at the same time it needs to note that the positive effects of education investment will be restricted by the economic structure and policy environment,and education expenditure policies should also be implemented in accordance with time and local conditions.展开更多
This paper selects seven indicators of financial revenue and housing sales price in recent 19 years in China,and uses SPSS and Excel to carry out descriptive statistics,independent sample t-test,correlation analysis a...This paper selects seven indicators of financial revenue and housing sales price in recent 19 years in China,and uses SPSS and Excel to carry out descriptive statistics,independent sample t-test,correlation analysis and regression analysis to comprehensively study the correlation between financial revenue and housing sales price in China,and establishes the relationship between financial revenue and housing sales price When the average selling price of commercial housing increases by one unit,the fiscal revenue will increase by 27.855 points.展开更多
文摘In this paper we firstly select main factors relating to urbanization level of Xiantao District in Hubei Province by main element, then, make model of urbanization level by analysis of multiple liner regression, and lastly predict its urbanization level
文摘In oil and gas exploration,elucidating the complex interdependencies among geological variables is paramount.Our study introduces the application of sophisticated regression analysis method at the forefront,aiming not just at predicting geophysical logging curve values but also innovatively mitigate hydrocarbon depletion observed in geochemical logging.Through a rigorous assessment,we explore the efficacy of eight regression models,bifurcated into linear and nonlinear groups,to accommodate the multifaceted nature of geological datasets.Our linear model suite encompasses the Standard Equation,Ridge Regression,Least Absolute Shrinkage and Selection Operator,and Elastic Net,each presenting distinct advantages.The Standard Equation serves as a foundational benchmark,whereas Ridge Regression implements penalty terms to counteract overfitting,thus bolstering model robustness in the presence of multicollinearity.The Least Absolute Shrinkage and Selection Operator for variable selection functions to streamline models,enhancing their interpretability,while Elastic Net amalgamates the merits of Ridge Regression and Least Absolute Shrinkage and Selection Operator,offering a harmonized solution to model complexity and comprehensibility.On the nonlinear front,Gradient Descent,Kernel Ridge Regression,Support Vector Regression,and Piecewise Function-Fitting methods introduce innovative approaches.Gradient Descent assures computational efficiency in optimizing solutions,Kernel Ridge Regression leverages the kernel trick to navigate nonlinear patterns,and Support Vector Regression is proficient in forecasting extremities,pivotal for exploration risk assessment.The Piecewise Function-Fitting approach,tailored for geological data,facilitates adaptable modeling of variable interrelations,accommodating abrupt data trend shifts.Our analysis identifies Ridge Regression,particularly when augmented by Piecewise Function-Fitting,as superior in recouping hydrocarbon losses,and underscoring its utility in resource quantification refinement.Meanwhile,Kernel Ridge Regression emerges as a noteworthy strategy in ameliorating porosity-logging curve prediction for well A,evidencing its aptness for intricate geological structures.This research attests to the scientific ascendancy and broad-spectrum relevance of these regression techniques over conventional methods while heralding new horizons for their deployment in the oil and gas sector.The insights garnered from these advanced modeling strategies are set to transform geological and engineering practices in hydrocarbon prediction,evaluation,and recovery.
文摘In recent years,the real estate industry has achieved significant progress,driving the development of related sectors and playing a crucial role in economic growth.However,rapid real estate market expansion has led to challenges,particularly concerning housing prices,which have drawn widespread societal attention.This article explores the theories of housing prices,analyzes factors influencing them,and conducts an empirical investigation of the impact of representative factors on ordinary residential prices.Using regression analysis and the entropy weight method,a mathematical model was developed to examine how various factors affect housing prices.
文摘A common current source, generally used to bias cross-coupled differential amplifiers in a transconductor, controls third harmonic distortion (HD3) poorly. Separate current sources are shown to provide better control on HD3) . In this paper, a detailed design and analysis is presented for a transconductor made using this biasing technique. The transconductor, in addition, is made to offer high Gm, low power dissipation and is designed for linearly tunable Gm with current mode load as one of the applications. The circuit exhibits HD3) of less than –43.7 dB, high current efficiency of 1.18 V-1 and Gm of 390 μS at 1 VGp-p @ 50 MHz. UMC 0.18 μm CMOS process technology is used for simulation at supply voltage of 1.8 V.
基金supported by National Nature Science Foundation of China(No.11861074,No.11371354 and N0.11301464)Key Laboratory of Random Complex Structures and Data Science,Chinese Academy of Sciences,Beijing 100190,China(No.2008DP173182)Applied Basic Research Project of Yunnan Province(No.2019FB138).
文摘As an extension of linear regression in functional data analysis, functional linear regression has been studied by many researchers and applied in various fields. However, in many cases, data is collected sequentially over time, for example the financial series, so it is necessary to consider the autocorrelated structure of errors in functional regression background. To this end, this paper considers a multiple functional linear model with autoregressive errors. Based on the functional principal component analysis, we apply the least square procedure to estimate the functional coefficients and autoregression coefficients. Under some regular conditions, we establish the asymptotic properties of the proposed estimators. A simulation study is conducted to investigate the finite sample performance of our estimators. A real example on China's weather data is applied to illustrate the validity of our model.
基金supported by the Key Technologies R&D Program of China during the 11th Five-Year Plan period (2008BAD98B03)
文摘Five statistical methods including simple correlation, multiple linear regression, stepwise regression, principal components, and path analysis were used to explore the relationship between leaf water use efficiency （WUE） and physiological traits （photosynthesis rate, stomatal conductance, transpiration rate, intercellular CO2 concentration, etc.） of 29 wheat cultivars. The results showed that photosynthesis rate, stomatal conductance, and transpiration rate were the most important leaf WUE parameters under drought condition. Based on the results of statistical analyses, principal component analysis could be the most suitable method to ascertain the relationship between leaf WUE and relative physiological traits. It is reasonable to assume that high leaf WUE wheat could be obtained by selecting breeding materials with high photosynthesis rate, low transpiration rate, and stomatal conductance under dry area.
文摘Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.
基金supported by the Research-Based Learning and Innovation Experimental Project for College Students in Hunan Province in 2018(Grant No.255-1097)Research-Based Learning and Innovation Experimental Project for Students in Changsha Medical University(Grant No.77-264).
文摘Objective: To analyze the characteristics and possible mechanism of lipid metabolism in pregnant rats with intestinal flora imbalance. Methods: A total of 129 sexually mature female SD rats were divided into three groups: non-pregnant group (untreated healthy rats), healthy pregnant group (natural insemination pregnant rats), and pregnant microflora disorder group (pregnant rats were given mixed antibiotics by gavage to build the modeling), with 43 rats in each group. The contents of TG, LDL, HDL and TC were detected by automatic biochemical analyzer, and the contents of SCD1, PGC-1 alpha, PEPCK, ApoE and MTTP genes were detected by fluorescence quantitative PCR technology. Regression analysis was used to explore the comprehensive influence of each gene on total cholesterol expression in rats. Principal component analysis was used to explore the internal mechanism of lipid metabolism in pregnant rats with intestinal flora disorder. Results: The contents of TG, TC, LDL and HDL were compared among the three groups of rats and the differences were statistically significant (P<0.05) . The expression levels of related genes (SCD1, PGC-1, PEPCK, ApoE, MTTP) in the three groups were statistically significant (P<0.05) . SCD1 content in the non-pregnant group, healthy pregnancy group, and disordered pregnancy group was (0.92±0.12) μg/mL, (1.20±0.15)μg/mL, and (1.53±0.20) μg/mL, respectively. PGC-1 alpha content in the non-pregnant group, healthy pregnancy group, and disordered pregnancy group was (1.34±0.21) μg/mL, (0.93±0.12) micron /mL, and (0.41±0.08) μg/mL, respectively. PEPCK content in the non-pregnant group, healthy pregnancy group, and disordered pregnancy group was (0.48±0.06) μg/mL, (0.35±0.09)μg/mL, and (0.22±0.05) μg/mL, and the differences were statistically significant (P<0.05) . Multivariate linear regression analysis showed that the influence of gene content on The effect of each gene content on TC content was in order from large to small: SCD1 (OR=4.572) , PGC-1 (OR=3.387) , PEPCK (OR=3.935) , ApoE (OR=3.597) , MTTP (OR=3.096) . The principal component analysis showed that three principal components could be extracted from five related genes of lipid metabolism in pregnant rats with intestinal dysbiosis: SCD1/PEPCK pathway (contribution rate: 36.28%) , PGC-1 /ApoE pathway (contribution rate: 30.42%) , and MTTP pathway (contribution rate: 15.37%) . Conclusion: After pregnancy, blood lipids in rats are significantly increased while the imbalance of intestinal flora will lead to decreased blood lipids. The disorder of lipid metabolism in pregnant rats with intestinal flora imbalance is mainly related to the disorder of gene expression, which further affects the functions of SCD1/PEPCK, PGC-1 /ApoE and MTTP pathways.
文摘In this article,it discusses the di£ferences in economic development between urban and rural areas and regions in our country from the perspective of education investment and fixed asset investment.Based on the provincial data of 31 provinces from 1999 to 2017 released by National Bureau of Statistics,it expends the Cobb-Douglas model and Lucas model,and analyses the data with multiple linear regression models.From the study,it finds that compared with investment in fixed assets,investment in education has a larger role in promoting economic development,which is more obvious in the underdeveloped central and western regions and rural areas.However,at the same time it needs to note that the positive effects of education investment will be restricted by the economic structure and policy environment,and education expenditure policies should also be implemented in accordance with time and local conditions.
基金Thank you for your valuable comments and suggestions.This research was supported by Yunnan applied basic research project(NO.2017FD150)Chuxiong Normal University General Research Project(NO.XJYB2001).
文摘This paper selects seven indicators of financial revenue and housing sales price in recent 19 years in China,and uses SPSS and Excel to carry out descriptive statistics,independent sample t-test,correlation analysis and regression analysis to comprehensively study the correlation between financial revenue and housing sales price in China,and establishes the relationship between financial revenue and housing sales price When the average selling price of commercial housing increases by one unit,the fiscal revenue will increase by 27.855 points.
