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Quantifying the Cooling Potential of Urban Tree Species:A Trait-Based Approach Using Envi-Met Simulations and Regression Analysis 认领 引用
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作者 Pallavi Sharma Ramkishore Singh 《Research in Ecology》 CAS 2026年第1期169-184,共16页
Urban Heat Island(UHI)effects are exacerbated by the expansion of impervious surfaces and loss of vegetation in urban centers,leading to elevated air and surface temperatures and reduced thermal comfort.Urban trees,th... Urban Heat Island(UHI)effects are exacerbated by the expansion of impervious surfaces and loss of vegetation in urban centers,leading to elevated air and surface temperatures and reduced thermal comfort.Urban trees,through shading and evapotranspiration,are among the most effective Nature-based Solutions(NbS)for passive cooling.This study assesses the cooling potential of selected tree species by analyzing their morphological and physiological traits using a combination of ENVI-met microclimate simulations and multiple regression modeling.A total of 15 urban tree species were selected from the literature and analyzed based on their dependency of their cooling efficacy.Later validated in urban setting by Envi-met simulations.Key traits,such as Leaf Area Index(LAI),canopy density,transpiration rate,tree height,rooting depth,and water availability,were analyzed.Multiple linear regression analysis was conducted to quantify the contribution of each trait to ambient temperature reduction.Results revealed that LAI(R2=0.76,p<0.001)and transpiration rate(R2=0.71,p<0.001)were the most significant predictors of daytime cooling,while canopy openness and tree height were more strongly correlated with nighttime heat dissipation.High-performing species,such as Ficus benghalensis,Azadirachta indica,and Samanea saman,demonstrated a maximum temperature reduction of 2.5-4.2℃,especially in compact,low-rise,and mid-rise zones.The study provides a quantitative trait-based framework for tree selection in urban greening initiatives and offers evidence to guide landscape planning and UHI mitigation strategies through scientifically informed plantation design. 展开更多
关键词 Urban Heat Island Cooling Efficacy of Tree Species Regression Analysis Envi-Met Simulations
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Regression analysis of squeezing-induced hybrid nanofluid flow in Darcy-Forchheimer porous medium 认领 引用
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作者 K.MUHAMMAD M.SARFRAZ 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2025年第1期193-208,共16页
This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates.One plate remains stationary,while the other moves downward at a squeezing veloci... This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates.One plate remains stationary,while the other moves downward at a squeezing velocity.The space between these plates contains a Darcy-Forchheimer porous medium.A mixture of water-based fluid with gold(Au)and silicon dioxide(Si O2)nanoparticles is formulated.In contrast to the conventional Fourier's heat flux equation,this study employs the Cattaneo-Christov heat flux equation.A uniform magnetic field is applied perpendicular to the flow direction,invoking magnetohydrodynamic(MHD)effects.Further,the model accounts for Joule heating,which is the heat generated when an electric current passes through the fluid.The problem is solved via NDSolve in MATHEMATICA.Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow,energy transport,and skin friction.The findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies.It is observed that the squeezing motion generates additional pressure gradients within the fluid,which enhances the flow rate but reduces the frictional drag.Consequently,the fluid is pushed more vigorously between the plates,increasing the flow velocity.As the fluid experiences higher flow rates due to the increased squeezing effect,it spends less time in the region between the plates.The thermal relaxation,however,abruptly changes the temperature,leading to a decrease in the temperature fluctuations. 展开更多
关键词 convective boundary condition Darcy-Forchheimer medium hybrid nanofuid Joule heating magnetohydrodynamic(MHD) numerical solution squeezing flow regression analysis
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Theoretical modeling of vectoring dual synthetic jet based on regression analysis 认领 引用 被引量：8
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作者 Zhijie ZHAO Zhenbing LUO +2 位作者 Xiong DENG Zhiyong LIU Shiqing LI 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2021年第3期1-12,共12页
The excellent vectoring characteristic of Dual Synthetic Jet(DSJ)provides a new control strategy for the active flow control,such as thrust vectoring control,large area cooling,separated flow control and so on.For inc... The excellent vectoring characteristic of Dual Synthetic Jet(DSJ)provides a new control strategy for the active flow control,such as thrust vectoring control,large area cooling,separated flow control and so on.For incompressible flow,the influence relation of source variables,such as structure parameters of actuators,driving parameters and material attributes of piezoelectric vibrating diaphragm,on the vectoring DSJ and a theoretical model are established based on theoretical and regression analysis,which are all verified by numerical simulations.The two synthetic jets can be deemed as a main flow with a higher jet velocity and a disturbing flow with a lower jet velocity.The results indicate that the influence factors contain the low-pressure area formed at the exit of the disturbing flow,which could promote the vectoring deflection,and the impact effect of the disturbing flow and the suppressive effect of the main flow with the effect of restraining the vectoring deflection.The vectoring angle is a complex parameter coupled by all source variables.The detailed theoretical model,whose error is controlled within 3.6 degrees,can be used to quantitatively assess the vectoring feature of DSJ and thus to provide a guidance for designing the control law applied in the active flow control. 展开更多
关键词 Dual synthetic jet Influence relation Regression analysis Theoretical model Vector
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DDM regression analysis of the in-situ stress field in a non-linear fault zone 认领 引用 被引量：11
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作者 Ke Li Ying-yi Wang Xing-chun Huang 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2012年第7期567-573,共7页
A multivariable regression analysis of the in-situ stress field, which considers the non-linear deformation behavior of faults in practical projects, is presented based on a newly developed three-dimensional displacem... A multivariable regression analysis of the in-situ stress field, which considers the non-linear deformation behavior of faults in practical projects, is presented based on a newly developed three-dimensional displacement discontinuity method （DDM） program. The Bar- ton-Bandis model and the Kulhaway model are adopted as the normal and the tangential deformation model of faults, respectively, where the Mohr-Coulomb failure criterion is satisfied. In practical projects, the values of the mechanical parameters of rock and faults are restricted in a bounded range for in-situ test, and the optimal mechanical parameters are obtained from this range by a loop. Comparing with the traditional finite element method （FEM）, the DDM regression results are more accurate. 展开更多
关键词 displacement discontinuity method （DDM） in-situ stress regression analysis faults rock
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Multiple regression analysis of risk factors related to radiation pneumonitis 认领 引用 被引量：5
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作者 Ling-Ling Shi Jiang-Hua Yang Hong-Fa Yao 《World Journal of Clinical Cases》 SCIE 2023年第5期1040-1048,共9页
BACKGROUND Radiation pneumonitis(RP)is a severe complication of thoracic radiotherapy that may lead to dyspnea and lung fibrosis,and negatively affects patients’quality of life.AIM To carry out multiple regression an... BACKGROUND Radiation pneumonitis(RP)is a severe complication of thoracic radiotherapy that may lead to dyspnea and lung fibrosis,and negatively affects patients’quality of life.AIM To carry out multiple regression analysis on the influencing factors of radiation pneumonitis.METHODS Records of 234 patients receiving chest radiotherapy in Huzhou Central Hospital(Huzhou,Zhejiang Province,China)from January 2018 to February 2021,and the patients were divided into either a study group or a control group based on the presence of radiation pneumonitis or not.Among them,93 patients with radiation pneumonitis were included in the study group and 141 without radiation pneumonitis were included in the control group.General characteristics,and radiation and imaging examination data of the two groups were collected and compared.Due to the statistical significance observed,multiple regression analysis was performed on age,tumor type,chemotherapy history,forced vital capacity(FVC),forced expiratory volume in the first second(FEV1),carbon monoxide diffusion volume(DLCO),FEV1/FVC ratio,planned target area(PTV),mean lung dose(MLD),total number of radiation fields,percentage of lung tissue in total lung volume(vdose),probability of normal tissue complications(NTCP),and other factors.RESULTS The proportions of patients aged≥60 years and those with the diagnosis of lung cancer and a history of chemotherapy in the study group were higher than those in the control group(P<0.05);FEV1,DLCO,and FEV1/FVC ratio in the study group were lower than those in the control group(P<0.05),while PTV,MLD,total field number,vdose,and NTCP were higher than in the control group(P<0.05).Logistic regression analysis showed that age,lung cancer diagnosis,chemotherapy history,FEV1,FEV1/FVC ratio,PTV,MLD,total number of radiation fields,vdose,and NTCP were risk factors for radiation pneumonitis.CONCLUSION We have identified patient age,type of lung cancer,history of chemotherapy,lung function,and radiotherapy parameters as risk factors for radiation pneumonitis.Comprehensive evaluation and examination should be carried out before radiotherapy to effectively prevent radiation pneumonitis. 展开更多
关键词 Radiation pneumonitis Influencing factors Radiotherapy Multiple regression analysis
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Regression analysis of major parameters affecting the intensity of coal and gas outbursts in laboratory 认领 引用 被引量：9
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作者 Geng Jiabo Xu Jiang +3 位作者 Nie Wen Peng Shoujian Zhang Chaolin Luo Xiaohang 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2017年第2期327-332,共6页
Estimating the intensity of outbursts of coal and gas is important as the intensity and frequency of outbursts of coal and gas tend to increase in deep mining. Fully understanding the major factors contributing to coa... Estimating the intensity of outbursts of coal and gas is important as the intensity and frequency of outbursts of coal and gas tend to increase in deep mining. Fully understanding the major factors contributing to coal and gas outbursts is significant in the evaluation of the intensity of the outburst. In this paper, we discuss the correlation between these major factors and the intensity of the outburst using Analysis of Variance(ANOVA) and Contingency Table Analysis(CTA). Regression analysis is used to evaluate the impact of these major factors on the intensity of outbursts based on physical experiments. Based on the evaluation, two simple models in terms of multiple linear and nonlinear regression were constructed for the prediction of the intensity of the outburst. The results show that the gas pressure and initial moisture in the coal mass could be the most significant factors compared to the weakest factor-porosity. The P values from Fisher's exact test in CTA are: moisture(0.019), geostress(0.290), porosity(0.650), and gas pressure(0.031). P values from ANOVA are moisture(0.094), geostress(0.077), porosity(0.420), and gas pressure(0.051). Furthermore, the multiple nonlinear regression model(RMSE: 3.870) is more accurate than the linear regression model(RMSE: 4.091). 展开更多
关键词 Coal and gas outburst Gas pressure Regression analysis ANOVA CTA
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Factor Decomposition and Regression Analysis of the Energy Related Carbon Emissions in Shandong, China: A Perspective of Industrial Structure 认领 引用 被引量：2
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作者 Weifeng Gong Baoqing Zhu +3 位作者 Chuanhui Wang Zhenyue Fan Mengzhen Zhao Liang Chen 《Energy Engineering》 EI 2021年第4期981-994,共14页
An in-depth study of the energy related carbon emissions has important practical significance for carbon emissions reduction and structural adjustment in Shandong Province and throughout China.Based on the perspective... An in-depth study of the energy related carbon emissions has important practical significance for carbon emissions reduction and structural adjustment in Shandong Province and throughout China.Based on the perspective of industrial structure,the expanded KAYA equation to measure the energy related carbon emissions of the primary industries(Resources and Agriculture)and secondary industries(Manufacturing and Construction)and tertiary industries(Retail and Service)was utilized in Shandong Province from 2011 to 2017.The carbon emissions among industries in Shandong Province were empirically analyzed using the Logarithmic Mean Divisia Index decomposition approach.The results were follows:(1)Under the three industrial dimensions,the energy structure effect and the energy intensity effect have a restraining influence on the carbon emissions of the three industries.(2)The development level effect and the employment scale effect play a pulling role in carbon emissions.(3)From the perspective of the employment structure effect of the primary industry,there is a restraining effect on carbon emissions,while the employment structure effects of the secondary and tertiary industries play a pulling role in carbon emissions,and the employment structure effect of the tertiary industry has a greater pulling effect on carbon emissions than the secondary industry. 展开更多
关键词 Carbon emissions industrial structure expanded KAYA equation LMDI decomposition regression analysis
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Prediction of cavity growth rate during underground coal gasification using multiple regression analysis 认领 引用 被引量：13
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作者 Mehdi Najafi Seyed Mohammad Esmaiel Jalali +1 位作者 Reza KhaloKakaie Farrokh Forouhandeh 《International Journal of Coal Science & Technology》 CAS 2015年第4期318-324,共7页
During underground coal gasification （UCG）, whereby coal is converted to syngas in situ, a cavity is formed in the coal seam. The cavity growth rate （CGR） or the moving rate of the gasification face is affected by... During underground coal gasification （UCG）, whereby coal is converted to syngas in situ, a cavity is formed in the coal seam. The cavity growth rate （CGR） or the moving rate of the gasification face is affected by controllable （operation pressure, gasification time, geometry of UCG panel） and uncontrollable （coal seam properties） factors. The CGR is usually predicted by mathematical models and laboratory experiments, which are time consuming, cumbersome and expensive. In this paper, a new simple model for CGR is developed using non-linear regression analysis, based on data from 1 l UCG field trials. The empirical model compares satisfactorily with Perkins model and can reliably predict CGR. 展开更多
关键词 Underground coal gasification （UCG） - Cavity growth rate . Multiple regression analysis ~ Empirical model
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Statistical Evaluation and Regression Analysis of Vehicle Sound Quality 认领 引用 被引量：2
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作者 王养军 舒歌群 卫海桥 《Transactions of Tianjin University》 EI CAS 2006年第4期297-302,共6页
A statistical approach to evaluate the subjective perception of the annoyance caused by the vehicle noise was presented in this paper. After recording the noises of Sanfeng, Huali and Xiali at speeds of 30, 40, 50, 60... A statistical approach to evaluate the subjective perception of the annoyance caused by the vehicle noise was presented in this paper. After recording the noises of Sanfeng, Huali and Xiali at speeds of 30, 40, 50, 60, 70 and 80 km/h respectively, the annoyance of the vehicle noises was evaluated in the testing room using paired comparison method, and the sound quality metrics and subjective annoyance were then distilled. Loudness, sharpness, roughness, periodicity and impulsiveness were selected for each of the vehicle noises. By correlation analysis method, it can be found that loudness has a higher correlation （0.91） with annoyance than other parameters. Meanwhile, sharpness, periodicity, roughness and impulsiveness have correlation with subjective perception with correlation coefficients being 0.84, -0.82, 0.62 and 0.87, respectively. The result of multiple regression analysis shows that calculated annoyance obtained by the regression equation can explain the perceptual annoyance and the regressed evaluation model is feasible to evaluate the sound quality of vehicle. 展开更多
关键词 vehicle noise sound quality annoyance paired comparison regression analysis
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Logistic Regression Analysis of Syndrome Essential Factors in Patients with Unstable Angina Pectoris 认领 引用 被引量：5
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作者 姚魁武 何庆勇 +1 位作者 藤菲 王阶 《Journal of Traditional Chinese Medicine》 SCIE CSCD 2011年第4期273-276,共4页
Objective: To explore the correlation between common syndrome essential factors and the symptoms and signs of unstable angina (UA). Methods: Eight hundred and fifteen patients with UA confirmed by coronary angiography... Objective: To explore the correlation between common syndrome essential factors and the symptoms and signs of unstable angina (UA). Methods: Eight hundred and fifteen patients with UA confirmed by coronary angiography were identified from several centers. Common syndrome essential factors were selected on the basis of expert experience. The correlations between common syndrome essential factors and symptoms and signs of UA were analyzed using binary logistic regression analysis. Results: The common syndrome essential factors in unstable angina were blood stasis, qi stagnation, phlegm turbidity, heat stagnancy, qi deficiency, yin deficiency, and yang deficiency. Symptoms such as chest pain, hypochondriac distention, ecchymosis, dark orbits, dark and purplish tongue, and tongue with ecchymosis and petechiae were significant diagnostic features of "blood stasis". Aversion to cold and cool limbs, weakness in the waist and knees, and clear abundant urine were significant diagnostic features of "yang deficiency". These results were in accordance with the understanding of traditional clinical Chinese medical practice. Conclusion: This clinical study analyzed the correlations between common syndrome essential factors and the symptoms and signs of unstable angina. The results provide the basis for establishing diagnostic criteria for syndrome essential factors. 展开更多
关键词 unstable angina syndrome essential factor logistic regression analysis
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Multiple regression analysis of the craniofacial region of Chinese Han people using linear and angular measurements based on MRI 认领 引用 被引量：1
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作者 Chengzhi Li Wei Wu +5 位作者 Bo Zhu Xuefeng Liu Ping Huang Zhenyuan Wang Ya Tuo Fu Ren 《Forensic Sciences Research》 2017年第1期34-39,共6页
The purpose of this study was to measure the craniofacial region of Chinese Han people in the linear and angular dimensions,and to analyse the effects on sex,age and body parameters(height and weight).All 250 individu... The purpose of this study was to measure the craniofacial region of Chinese Han people in the linear and angular dimensions,and to analyse the effects on sex,age and body parameters(height and weight).All 250 individuals(86 males,164 females)underwent a three-dimensional magnetic resonance imaging(MRI)scan,and the MRI data were imported into VG Studio MAX 2.2 software.Each linear and angular measurement in the craniofacial region was processed directly.Using SPSS 20.0 software,nine multiple regression equations were constructed,and all the adjusted R2values were statistically significant(0.031-0.311).Multiple regression analysis showed that most craniofacial measurements of Chinese people were significantly correlated with height,weight or age.The multiple regression equations constructed will be helpful in anthropometric analysis and forensic inference. 展开更多
关键词 Forensic science forensic anthropology anthropometry regression analysis magnetic resonance imaging
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Regression analysis and its application to oil and gas exploration:A case study of hydrocarbon loss recovery and porosity prediction,China 认领 引用 被引量：1
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作者 Yang Li Xiaoguang Li +3 位作者 Mingyu Guo Chang Chen Pengbo Ni Zijian Huang 《Energy Geoscience》 EI 2024年第4期240-252,共13页
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
关键词 Regression analysis Oil and gas exploration Multiple linear regression model Nonlinear regression model Hydrocarbon loss recovery Porosity prediction
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Regression Analysis of the Number of Association Rules 认领 引用 被引量：2
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作者 Wei-Guo Yi Ming-Yu Lu Zhi Liu 《International Journal of Automation and computing》 2011年第1期78-82,共5页
The typical model, which involves the measures： support, confidence, and interest, is often adapted to mining association rules. In the model, the related parameters are usually chosen by experience; consequently, th... The typical model, which involves the measures： support, confidence, and interest, is often adapted to mining association rules. In the model, the related parameters are usually chosen by experience; consequently, the number of useful rules is hard to estimate. If the number is too large, we cannot effectively extract the meaningful rules. This paper analyzes the meanings of the parameters and designs a variety of equations between the number of rules and the parameters by using regression method. Finally, we experimentally obtain a preferable regression equation. This paper uses multiple correlation coeficients to test the fitting efiects of the equations and uses significance test to verify whether the coeficients of parameters are significantly zero or not. The regression equation that has a larger multiple correlation coeficient will be chosen as the optimally fitted equation. With the selected optimal equation, we can predict the number of rules under the given parameters and further optimize the choice of the three parameters and determine their ranges of values. 展开更多
关键词 Association rules regression analysis multiple correlation coeficients interest support confidence.
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New empirical model to evaluate groundwater flow into circular tunnel using multiple regression analysis 认领 引用 被引量：7
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作者 Farhadian Hadi Katibeh Homayoon 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2017年第3期415-421,共7页
There are various analytical, empirical and numerical methods to calculate groundwater inflow into tun- nels excavated in rocky media. Analytical methods have been widely applied in prediction of groundwa- ter inflow ... There are various analytical, empirical and numerical methods to calculate groundwater inflow into tun- nels excavated in rocky media. Analytical methods have been widely applied in prediction of groundwa- ter inflow to tunnels due to their simplicity and practical base theory. Investigations show that the real amount of water infiltrating into jointed tunnels is much less than calculated amount using analytical methods and obtained results are very dependent on tunnel＇s geometry and environmental situations. In this study, using multiple regression analysis, a new empirical model for estimation of groundwater seepage into circular tunnels was introduced. Our data was acquired from field surveys and laboratory analysis of core samples. New regression variables were defined after perusing single and two variables relationship between groundwater seepage and other variables. Finally, an appropriate model for estima- tion of leakage was obtained using the stepwise algorithm. Statistics like R, R2, R2e and the histogram of residual values in the model represent a good reputation and fitness for this model to estimate the groundwater seepage into tunnels. The new experimental model was used for the test data and results were satisfactory. Therefore, multiple regression analysis is an effective and efficient way to estimate the groundwater seeoage into tunnels. 展开更多
关键词 Groundwater inflow Analytical equation Multiple regression analysis Stepwise algorithm Tunnel
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Regression Analysis of Initial Stress Field Around Faults Based on Fault Throw by Displacement Discontinuity Method 认领 引用 被引量：1
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作者 李科 王颖轶 黄醒春 《Journal of Shanghai Jiaotong university(Science)》 EI 2013年第4期474-478,共5页
The back analysis of initial stress is usually based on measured stress values, but the measuring of initial stress demands substantial investment. Therefore, amounts of underground engineering have no measured initia... The back analysis of initial stress is usually based on measured stress values, but the measuring of initial stress demands substantial investment. Therefore, amounts of underground engineering have no measured initial stress data, such as tunneling engineering. Focusing on this problem, a new back analysis method which does not need measured initial stress data is developed. The fault is assumed to be caused by initial load, the displacement discontinuity method (DDM) which considered non-linear fault is adopted to establish a numerical model of the engineering site, and the multivariable regression analysis of the initial stress field around the faults is carried out based on the fault throw. The result shows that the initial stress field around the faults is disturbed significantly, stress concentration appears in the tip zone, the regressive fault throw matches the measured values well, and the regressive initial stress field is reliable. 展开更多
关键词 displacement discontinuity method （DDM） fault initial stress field regression analysis numerical simulation
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Stability of mine ventilation system based on multiple regression analysis 认领 引用 被引量：14
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作者 JIA Ting-gui LIU Jian 《Mining Science and Technology》 2009年第4期463-466,共4页
In order to overcome the disadvantages of diagonal connection structures that are complex and for which it is difficult to derive the discriminant of the airflow directions of airways, we have applied a multiple regre... In order to overcome the disadvantages of diagonal connection structures that are complex and for which it is difficult to derive the discriminant of the airflow directions of airways, we have applied a multiple regression method to analyze the effect, of changing the rules of mine airflows, on the stability of a mine ventilation system. The amount of air （ Qj ） is determined for the major airway and an optimum regression equation was derived for Qi as a function of the independent variable （ Ri ）, i.e., the venti- lation resistance between different airways. Therefore, corresponding countermeasures are proposed according to the changes in airflows. The calculated results agree very well with our practical situation, indicating that multiple regression analysis is simple, quick and practical and is therefore an effective method to analyze the stability of mine ventilation systems. 展开更多
关键词 ventilation network stability diagonal connection, multiple regression analysis
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Biological stability in drinking water: a regression analysis of influencing factors 认领 引用 被引量：1
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作者 LUWei ZHANGXiao-jian 《Journal of Environmental Sciences》 SCIE EI CAS 2005年第3期395-398,共4页
Some parameters, such as assimilable organic carbon(AOC), chloramine residual, water temperature, and water residence time, were measured in drinking water from distribution systems in a northern city of China. The me... Some parameters, such as assimilable organic carbon(AOC), chloramine residual, water temperature, and water residence time, were measured in drinking water from distribution systems in a northern city of China. The measurement results illustrate that when chloramine residual is more than 0.3 mg/L or AOC content is below 50 μg/L, the biological stability of drinking water can be controlled. Both chloramine residual and AOC have a good relationship with Heterotrophic Plate Counts(HPC)(log value), the correlation coefficient was -0.64 and 0.33, respectively. By regression analysis of the survey data, a statistical equation is presented and it is concluded that disinfectant residual exerts the strongest influence on bacterial growth and AOC is a suitable index to assess the biological stability in the drinking water. 展开更多
关键词 AOC biological stability HPC residual chloramines regression analysis
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Heteroscedastic regression analysis method for mixed data 认领 引用 被引量：1
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作者 FU Hui-min YUE Xiao-rui 《航空动力学报》 EI CAS CSCD 北大核心 2011年第4期721-726,共6页
The heteroscedastic regression model was established and the heteroscedastic regression analysis method was presented for mixed data composed of complete data,type-Ⅰ censored data and type-Ⅱ censored data from the l... The heteroscedastic regression model was established and the heteroscedastic regression analysis method was presented for mixed data composed of complete data,type-Ⅰ censored data and type-Ⅱ censored data from the location-scale distribution.The best unbiased estimations of regression coefficients,as well as the confidence limits of the location parameter and scale parameter were given.Furthermore,the point estimations and confidence limits of percentiles were obtained.Thus,the traditional multiple regression analysis method which is only suitable to the complete data from normal distribution can be extended to the cases of heteroscedastic mixed data and the location-scale distribution.So the presented method has a broad range of promising applications. 展开更多
关键词 heteroscedastic regression analysis censored data performance test life prediction reliability analysis
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COX MULTIVARIATE REGRESSION ANALYSIS OF RECURRENCE FACTORS FOR COLONIC CARCINOMA 认领 引用
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作者 杜寒松 王国斌 +2 位作者 秦青平 夏玉春 司徒光伟 《Chinese Journal of Cancer Research》 CAS 2004年第4期274-278,共5页
Objective: To determine the independent prognostic factors in the recurrence of colonic carcinoma after curative resection. Methods: Two hundred and one patients undergoing curative resections for colonic carcinoma we... Objective: To determine the independent prognostic factors in the recurrence of colonic carcinoma after curative resection. Methods: Two hundred and one patients undergoing curative resections for colonic carcinoma were investigated by univariate and Cox multivariate regression analyses. Ten factors contributed to the rate were analyzed. Results: Dukes stages, obstruction, postoperative chemotherapy as well as the growth manner of the tumor were significantly associated with the recurrence rate of colonic carcinoma (P<0.05) by univariate analysis, while Dukes stages, obstruction, and postoperative chemotherapy were significant factors by the multivariate analysis. Conclusion: Dukes stages, obstruction, and postoperative chemotherapy are independent prognostic factors in the recurrence of colonic carcinoma. 展开更多
关键词 Cox multivariate regression analysis Recurrence factors Colonic carcinoma Diagnosis
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An Adaptive Design for Six Sigma(ADFSS): a Simulated Annealing and Regression Analysis Embedded Approach 认领 引用
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作者 李蓓智 吴珊珊 +1 位作者 杨建国 SHUKLA S K 《Journal of Donghua University(English Edition)》 EI CAS 2011年第5期491-498,共8页
Design for six sigma （DFSS） is a powerful approach of designing products, processes, and services with the objective of meeting the needs of customers in a cost-effective maimer. DFSS activities are classified into ... Design for six sigma （DFSS） is a powerful approach of designing products, processes, and services with the objective of meeting the needs of customers in a cost-effective maimer. DFSS activities are classified into four major phases viz. identify, design, optimize, and validate （IDOV）. And an adaptive design for six sigma （ADFSS） incorporating the traits of artifidai intelligence and statistical techniques is presented. In the identify phase of the ADFSS, fuzzy relation measures between customer attributes （CAs） and engineering characteristics （ECs） as well as fuzzy correlation measures among ECs are determined with the aid of two fuzzy logic controllers （FLCs）. These two measures are then used to establish the cumulative impact factor for ECs. In the next phase （ i. e. design phase）, a transfer function is developed with the aid of robust multiple nonlinear regression analysis. Furthermore, 1this transfer function is optimized with the simulated annealing （ SA ） algorithm in the optimize phase. In the validate phase, t-test is conducted for the validation of the design resulted in earlier phase. Finally, a case study of a hypothetical writing instrument is simulated to test the efficacy of the proposed ADFSS. 展开更多
关键词 design for six sigma （DFSS） fuzzy logic eontroller（ FLC） robust multiple nonlinear regression analysis simulated annealing（SA）
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