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
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
[Objectives] To analyze the influencing factors of fixed defects in patients with catheter fixation in clinical nursing work, in order to provide the best catheter fixation nursing plan for patients.[Methods] 176 inpa...[Objectives] To analyze the influencing factors of fixed defects in patients with catheter fixation in clinical nursing work, in order to provide the best catheter fixation nursing plan for patients.[Methods] 176 inpatients with indwelling catheter from surgical system of Taihe Hospital in Shiyan City from August 2022 to March 2023 were selected. Using a retrospective analysis method, the influencing factors of catheter fixation defects in the study subjects were divided into two categories based on objective characteristics: type I non modifiable influencing factors and type II modifiable influencing factors. Using the standard for catheter fixation defects, whether the patient had catheter fixation defects was determined. After classified and statistically analyzed item by item, binary Logistic multiple regression analysis was used to identify the influencing factors.[Results] The occurrence of catheter fixation defects in patients with catheter fixation was related to factors such as whether the patient was evaluated before fixation, whether the fixation method was standardized and systematic, whether there was sufficient communication between nurses and patients, and the patient s knowledge of catheter fixation. It was also influenced by factors such as the patient s age, catheterization site, catheterization number, catheterization duration, where there was a consciousness disorder, educational level, and external environmental temperature.[Conclusions] Early attention to the key factors affecting patients with catheter fixation defects can effectively prevent adverse factors and provide patients with the best catheter fixation nursing plan to improve nursing quality.展开更多
Objective To explore the clinical characteristics and methods for syndrome differentiation prediction,as well as to construct a predictive model for Qi deficiency and blood stasis syndrome in patients with acute ische...Objective To explore the clinical characteristics and methods for syndrome differentiation prediction,as well as to construct a predictive model for Qi deficiency and blood stasis syndrome in patients with acute ischemic stroke(AIS).Methods This study employed a retrospective case-control design to analyze patients with AIS who received inpatient treatment at the Neurology Department of The First Hospital of Hunan University of Chinese Medicine from January 1,2013 to December 31,2022.AIS patients meeting the diagnostic criteria for Qi deficiency and blood stasis syndrome were stratified into case group,while those without Qi deficiency and blood stasis syndrome were stratified into control group.The demographic characteristics(age and gender),clinical parameters[time from onset to admission,National Institutes of Health Stroke Scale(NIHSS)score,and blood pressure],past medical history,traditional Chinese medicine(TCM)diagnostic characteristics(tongue and pulse),neurological symptoms and signs,imaging findings[magnetic resonance imaging-diffusion weighted imaging(MRI-DWI)],and biochemical indicators of the two groups were collected and compared.The indicators with statistical difference(P<0.05)in univariate analysis were included in multivariate logistic regression analysis to evaluate their predictive value for the diagnosis of Qi deficiency and blood stasis syndrome,and the predictive model was constructed by receiver operating characteristic(ROC)curve analysis.Results The study included 1035 AIS patients,with 404 cases in case group and 631 cases in control group.Compared with control group,patients in case group were significantly older,had extended onset-to-admission time,lower diastolic blood pressure,and lower NIHSS scores(P<0.05).Case group showed lower incidence of hypertension history(P<0.05).Regarding tongue and pulse characteristics,pale and dark tongue colors,white tongue coating,fine pulse,astringent pulse,and sinking pulse were more common in case group.Imaging examinations demonstrated higher proportions of centrum semiovale infarction,cerebral atrophy,and vertebral artery stenosis in case group(P<0.05).Among biochemical indicators,case group showed higher proportions of elevated fasting blood glucose and glycated hemoglobin(HbA1c),while lower proportions of elevated white blood cell count,reduced hemoglobin,and reduced high-density lipoprotein cholesterol(HDL-C)(P<0.05).Multivariate logistic regression analysis identified significant predictors for Qi deficiency and blood stasis syndrome including:fine pulse[odds ratio(OR)=4.38],astringent pulse(OR=3.67),superficial sensory abnormalities(OR=1.86),centrum semiovale infarction(OR=1.57),cerebral atrophy(OR=1.55),vertebral artery stenosis(OR=1.62),and elevated HbA1c(OR=3.52).The ROC curve analysis of the comprehensive prediction model yielded an area under the curve(AUC)of 0.878[95%confidence interval(CI)=0.855-0.900].Conclusion This study finds out that Qi deficiency and blood stasis syndrome represents one of the primary types of AIS.Fine pulse,astringent pulse,superficial sensory abnormalities,centrum semiovale infarction,cerebral atrophy,vertebral artery stenosis,elevated blood glucose,elevated HbA1c,pale and dark tongue colors,and white tongue coating are key objective diagnostic indicators for the syndrome differentiation of AIS with Qi deficiency and blood stasis syndrome.Based on these indicators,a syndrome differentiation prediction model has been developed,offering a more objective basis for clinical diagnosis,and help to rapidly identify this syndrome in clinical practice and reduce misdiagnosis and missed diagnosis.展开更多
Taking into account the characteristics of non-Newtonian fluids and the influence of latent heat of wax crystallization,this study establishes physical and mathematical models for the synergy of tubular heating and me...Taking into account the characteristics of non-Newtonian fluids and the influence of latent heat of wax crystallization,this study establishes physical and mathematical models for the synergy of tubular heating and mechanical stirring during the waxy crude oil heating process.Numerical calculations are conducted using the sliding grid technique and FVM.The focus of this study is on the impact of stirring rate(τ),horizontal deflection angle(θ1),vertical deflection angle(θ2),and stirring diameter(D)on the heating effect of crude oil.Our results show that asτincreases from 200 rpm to 500 rpm and D increases from 400 mm to 600 mm,there is an improvement in the average crude oil temperature and temperature uniformity.Additionally,heating efficiency increases by 0.5%and 1%,while the volume of the low-temperature region decreases by 57.01 m^(3) and 36.87 m3,respectively.Asθ1 andθ2 increase from 0°to 12°,the average crude oil temperature,temperature uniformity,and heating efficiency decrease,while the volume of the low-temperature region remains basically the same.Grey correlation analysis is used to rank the importance of stirring parameters in the following order:τ>θ1>θ2>D.Subsequently,multiple regression analysis is used to quantitatively describe the relationship between different stirring parameters and heat transfer evaluation indices through equations.Finally,based on entropy generation minimization,the stirring parameters with optimal heat transfer performance are obtained when τ=350 rpm,θ1=θ2=0°,and D=500 mm.展开更多
[Objective] The research aimed to study the significant influence factors of the population variations of oriental fruit fly. [Method] Using stepwise regression analysis, the population variations law of oriental frui...[Objective] The research aimed to study the significant influence factors of the population variations of oriental fruit fly. [Method] Using stepwise regression analysis, the population variations law of oriental fruit fly in Jianshui County of Yunnan province and the meteorological factors that caused its occurrence were analyzed. And the regression model was built. Finally, the regression model was tested on the basis of the data in Jianshui County of Yunnan Province during 2004-2006.[Result] The main meteorological factors that influenced the occurrence of oriental fruit fly were relative humidity, the lowest monthly temperature and rainfall. [Conclusion] This study will provide certain reference for the prediction researches on the time, quantity and occurrence peak of oriental fruit fly.展开更多
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
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
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
Near infrared reflectance spectroscopy （NIRS）, a non-destructive measurement technique, was combined with partial least squares regression discrimiant analysis （PLS-DA） to discriminate the transgenic （TCTP and mi...Near infrared reflectance spectroscopy （NIRS）, a non-destructive measurement technique, was combined with partial least squares regression discrimiant analysis （PLS-DA） to discriminate the transgenic （TCTP and mi166） and wild type （Zhonghua 11） rice. Furthermore, rice lines transformed with protein gene （OsTCTP） and regulation gene （Osmi166） were also discriminated by the NIRS method. The performances of PLS-DA in spectral ranges of 4 000-8 000 cm-1 and 4 000-10 000 cm-1 were compared to obtain the optimal spectral range. As a result, the transgenic and wild type rice were distinguished from each other in the range of 4 000-10 000 cm-1, and the correct classification rate was 100.0% in the validation test. The transgenic rice TCTP and mi166 were also distinguished from each other in the range of 4 000-10 000 cm-1, and the correct classification rate was also 100.0%. In conclusion, NIRS combined with PLS-DA can be used for the discrimination of transgenic rice.展开更多
Four samples from a Permian reservoir in the Ordos Basin of North China were separated into twelve fractions in grain sizes of 〈0.5, 0.5-1 and 1-2 μm. Using the ^40Ar-^39Ar step-heating method, all of the fractions ...Four samples from a Permian reservoir in the Ordos Basin of North China were separated into twelve fractions in grain sizes of 〈0.5, 0.5-1 and 1-2 μm. Using the ^40Ar-^39Ar step-heating method, all of the fractions essentially yielded plateau ages ranging from 172.5 to 217.1 Ma. These scattered plateau ages might not have been obtained from pure diagenetic illites but from mixed clay minerals, although the samples were disaggregated using a gentle freeze-thaw cycle to free them of non-clay minerals. A regional thermal event, as suggested by several proxies, led to intensive iHitization as a distinct diagenetic process when the Yanshanian Movement triggered magmatism around the entire North China Block during the Jurassic to Cretaceous. Thermal illites formed during a short time period, whereas detrital illites came from various sources. The scattered plateau ages could have resulted from mixed degassing of thermal and detrital illites. Within one sample, the plateau ages decrease with the diminution of grain sizes, but it is difficult to extrapolate to the detrital-illite-free ages. Because the plateau age is a mixture of ages for thermal and detrital illites, this regression analysis studies the dependence of the plateau ages on the synthetic values of contents and ages of detrital illites instead of on the grain sizes. Comparing the samples to one another, the plateau ages show the same trend among the different grain sizes. Weighted by the contents and ages of detrital illites, linear regression analysis revealed the relationship between the plateau ages and the relative weight proportions. Based on iterated calculations, a thermal event age and a set of weight proportions were derived. The regressed thermal event age is 163.3±1.6 Ma, which coincides with regional thermal activities and links to gas accumulation.展开更多
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
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
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
Vehicle traveling time prediction is an important part of the research of intelligent transportation system. By now, there have been various kinds of methods for vehicle traveling time prediction. But few consider bot...Vehicle traveling time prediction is an important part of the research of intelligent transportation system. By now, there have been various kinds of methods for vehicle traveling time prediction. But few consider both aspects of time and space. In this paper, a vehicle traveling time prediction method based on grey theory （GT） and linear regression analysis （LRA） is presented. In aspects of time, we use the history data sequence of bus speed on a certain road to predict the future bus speed on that road by GT. And in aspects of space, we calculate the traffic affecting factors between various roads by LRA. Using these factors we can predict the vehicle＇s speed at the lower road if the vehicle＇s speed at the current road is known. Finally we use time factor and space factor as the weighting factors of the two results predicted by GT and LRA respectively to find the final result, thus calculating the vehicle＇s traveling time. The method also considers such factors as dwell time, thus making the prediction more accurate.展开更多
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
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
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
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
Breakwaters have been built throughout the centuries for the coastal protection and the port development,but changes occurred in their layout and criteria used for the design.Quarter circle breakwater(QBW)is a new typ...Breakwaters have been built throughout the centuries for the coastal protection and the port development,but changes occurred in their layout and criteria used for the design.Quarter circle breakwater(QBW)is a new type evolved having advantages of both caisson type and perforated type breakwaters.The present study extracts the effect of change in the percentage of perforations on the stable conditions of seaside perforated QBW by using various physical models.The results were graphically analyzed using dimensionless parameters and it was concluded that there is a reduction in dimensionless stability parameter with an increase in steepness of the wave and change in water depth to the height of breakwater structure.Multiple non–linear regression analysis was done and the equation for the best fit curve with a higher regression coefficient was obtained by using Excel statistical software—XLSTAT.展开更多
文摘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.
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[Objectives] To analyze the influencing factors of fixed defects in patients with catheter fixation in clinical nursing work, in order to provide the best catheter fixation nursing plan for patients.[Methods] 176 inpatients with indwelling catheter from surgical system of Taihe Hospital in Shiyan City from August 2022 to March 2023 were selected. Using a retrospective analysis method, the influencing factors of catheter fixation defects in the study subjects were divided into two categories based on objective characteristics: type I non modifiable influencing factors and type II modifiable influencing factors. Using the standard for catheter fixation defects, whether the patient had catheter fixation defects was determined. After classified and statistically analyzed item by item, binary Logistic multiple regression analysis was used to identify the influencing factors.[Results] The occurrence of catheter fixation defects in patients with catheter fixation was related to factors such as whether the patient was evaluated before fixation, whether the fixation method was standardized and systematic, whether there was sufficient communication between nurses and patients, and the patient s knowledge of catheter fixation. It was also influenced by factors such as the patient s age, catheterization site, catheterization number, catheterization duration, where there was a consciousness disorder, educational level, and external environmental temperature.[Conclusions] Early attention to the key factors affecting patients with catheter fixation defects can effectively prevent adverse factors and provide patients with the best catheter fixation nursing plan to improve nursing quality.
基金National Natural Science Foundation of China(U22A20377)Natural Science Foundation of Hunan Province of China(23C0168).
文摘Objective To explore the clinical characteristics and methods for syndrome differentiation prediction,as well as to construct a predictive model for Qi deficiency and blood stasis syndrome in patients with acute ischemic stroke(AIS).Methods This study employed a retrospective case-control design to analyze patients with AIS who received inpatient treatment at the Neurology Department of The First Hospital of Hunan University of Chinese Medicine from January 1,2013 to December 31,2022.AIS patients meeting the diagnostic criteria for Qi deficiency and blood stasis syndrome were stratified into case group,while those without Qi deficiency and blood stasis syndrome were stratified into control group.The demographic characteristics(age and gender),clinical parameters[time from onset to admission,National Institutes of Health Stroke Scale(NIHSS)score,and blood pressure],past medical history,traditional Chinese medicine(TCM)diagnostic characteristics(tongue and pulse),neurological symptoms and signs,imaging findings[magnetic resonance imaging-diffusion weighted imaging(MRI-DWI)],and biochemical indicators of the two groups were collected and compared.The indicators with statistical difference(P<0.05)in univariate analysis were included in multivariate logistic regression analysis to evaluate their predictive value for the diagnosis of Qi deficiency and blood stasis syndrome,and the predictive model was constructed by receiver operating characteristic(ROC)curve analysis.Results The study included 1035 AIS patients,with 404 cases in case group and 631 cases in control group.Compared with control group,patients in case group were significantly older,had extended onset-to-admission time,lower diastolic blood pressure,and lower NIHSS scores(P<0.05).Case group showed lower incidence of hypertension history(P<0.05).Regarding tongue and pulse characteristics,pale and dark tongue colors,white tongue coating,fine pulse,astringent pulse,and sinking pulse were more common in case group.Imaging examinations demonstrated higher proportions of centrum semiovale infarction,cerebral atrophy,and vertebral artery stenosis in case group(P<0.05).Among biochemical indicators,case group showed higher proportions of elevated fasting blood glucose and glycated hemoglobin(HbA1c),while lower proportions of elevated white blood cell count,reduced hemoglobin,and reduced high-density lipoprotein cholesterol(HDL-C)(P<0.05).Multivariate logistic regression analysis identified significant predictors for Qi deficiency and blood stasis syndrome including:fine pulse[odds ratio(OR)=4.38],astringent pulse(OR=3.67),superficial sensory abnormalities(OR=1.86),centrum semiovale infarction(OR=1.57),cerebral atrophy(OR=1.55),vertebral artery stenosis(OR=1.62),and elevated HbA1c(OR=3.52).The ROC curve analysis of the comprehensive prediction model yielded an area under the curve(AUC)of 0.878[95%confidence interval(CI)=0.855-0.900].Conclusion This study finds out that Qi deficiency and blood stasis syndrome represents one of the primary types of AIS.Fine pulse,astringent pulse,superficial sensory abnormalities,centrum semiovale infarction,cerebral atrophy,vertebral artery stenosis,elevated blood glucose,elevated HbA1c,pale and dark tongue colors,and white tongue coating are key objective diagnostic indicators for the syndrome differentiation of AIS with Qi deficiency and blood stasis syndrome.Based on these indicators,a syndrome differentiation prediction model has been developed,offering a more objective basis for clinical diagnosis,and help to rapidly identify this syndrome in clinical practice and reduce misdiagnosis and missed diagnosis.
基金supported by the National Natural Science Foundation of China(Grant no.52304065)China Postdoctoral Science Foundation(Grant no.2022MD723759).
文摘Taking into account the characteristics of non-Newtonian fluids and the influence of latent heat of wax crystallization,this study establishes physical and mathematical models for the synergy of tubular heating and mechanical stirring during the waxy crude oil heating process.Numerical calculations are conducted using the sliding grid technique and FVM.The focus of this study is on the impact of stirring rate(τ),horizontal deflection angle(θ1),vertical deflection angle(θ2),and stirring diameter(D)on the heating effect of crude oil.Our results show that asτincreases from 200 rpm to 500 rpm and D increases from 400 mm to 600 mm,there is an improvement in the average crude oil temperature and temperature uniformity.Additionally,heating efficiency increases by 0.5%and 1%,while the volume of the low-temperature region decreases by 57.01 m^(3) and 36.87 m3,respectively.Asθ1 andθ2 increase from 0°to 12°,the average crude oil temperature,temperature uniformity,and heating efficiency decrease,while the volume of the low-temperature region remains basically the same.Grey correlation analysis is used to rank the importance of stirring parameters in the following order:τ>θ1>θ2>D.Subsequently,multiple regression analysis is used to quantitatively describe the relationship between different stirring parameters and heat transfer evaluation indices through equations.Finally,based on entropy generation minimization,the stirring parameters with optimal heat transfer performance are obtained when τ=350 rpm,θ1=θ2=0°,and D=500 mm.
基金Supported by National Key Technology R&D Program in the11th Five Year Plan of China(2006BAD10A14)~~
文摘[Objective] The research aimed to study the significant influence factors of the population variations of oriental fruit fly. [Method] Using stepwise regression analysis, the population variations law of oriental fruit fly in Jianshui County of Yunnan province and the meteorological factors that caused its occurrence were analyzed. And the regression model was built. Finally, the regression model was tested on the basis of the data in Jianshui County of Yunnan Province during 2004-2006.[Result] The main meteorological factors that influenced the occurrence of oriental fruit fly were relative humidity, the lowest monthly temperature and rainfall. [Conclusion] This study will provide certain reference for the prediction researches on the time, quantity and occurrence peak of oriental fruit fly.
基金financially supported by the Western Transport Technical Project of the Ministry of Transport, China (No. 2009318000046)
文摘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.
基金Project F010206 supported by the National Natural Science Foundation of China
文摘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.
基金supported by the National Natural Science Foundation of China(Nos.11972369 and 11872374)。
文摘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.
基金supported by the projects under the Innovation Team of the Safety Standards and Testing Technology for Agricultural Products of Zhejiang Province, China (Grant No.2010R50028)the National Key Technologies R&D Program of China during the 11th Five-Year Plan Period (Grant No.2006BAK02A18)
文摘Near infrared reflectance spectroscopy （NIRS）, a non-destructive measurement technique, was combined with partial least squares regression discrimiant analysis （PLS-DA） to discriminate the transgenic （TCTP and mi166） and wild type （Zhonghua 11） rice. Furthermore, rice lines transformed with protein gene （OsTCTP） and regulation gene （Osmi166） were also discriminated by the NIRS method. The performances of PLS-DA in spectral ranges of 4 000-8 000 cm-1 and 4 000-10 000 cm-1 were compared to obtain the optimal spectral range. As a result, the transgenic and wild type rice were distinguished from each other in the range of 4 000-10 000 cm-1, and the correct classification rate was 100.0% in the validation test. The transgenic rice TCTP and mi166 were also distinguished from each other in the range of 4 000-10 000 cm-1, and the correct classification rate was also 100.0%. In conclusion, NIRS combined with PLS-DA can be used for the discrimination of transgenic rice.
基金supported by the National Natural Science Foundation of China(No.40572081)the Chinese Academy of Sciences(No.KZCX1-SW-18)
文摘Four samples from a Permian reservoir in the Ordos Basin of North China were separated into twelve fractions in grain sizes of 〈0.5, 0.5-1 and 1-2 μm. Using the ^40Ar-^39Ar step-heating method, all of the fractions essentially yielded plateau ages ranging from 172.5 to 217.1 Ma. These scattered plateau ages might not have been obtained from pure diagenetic illites but from mixed clay minerals, although the samples were disaggregated using a gentle freeze-thaw cycle to free them of non-clay minerals. A regional thermal event, as suggested by several proxies, led to intensive iHitization as a distinct diagenetic process when the Yanshanian Movement triggered magmatism around the entire North China Block during the Jurassic to Cretaceous. Thermal illites formed during a short time period, whereas detrital illites came from various sources. The scattered plateau ages could have resulted from mixed degassing of thermal and detrital illites. Within one sample, the plateau ages decrease with the diminution of grain sizes, but it is difficult to extrapolate to the detrital-illite-free ages. Because the plateau age is a mixture of ages for thermal and detrital illites, this regression analysis studies the dependence of the plateau ages on the synthetic values of contents and ages of detrital illites instead of on the grain sizes. Comparing the samples to one another, the plateau ages show the same trend among the different grain sizes. Weighted by the contents and ages of detrital illites, linear regression analysis revealed the relationship between the plateau ages and the relative weight proportions. Based on iterated calculations, a thermal event age and a set of weight proportions were derived. The regressed thermal event age is 163.3±1.6 Ma, which coincides with regional thermal activities and links to gas accumulation.
文摘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.
文摘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.
基金provided by the Natural Science Foundation Project(Key)of Chongqing(No.cstc2013jjB0012)the National Natural Science Foundation of China(No.51434003)the National Natural Science Foundation of China(No.51474040)
文摘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).
基金the National Natural Science Foundation of China (No. 50575145)the National High Technology Research and Development Program (863) of China(Nos. 2006AA04Z432 and 2007AA04Z419)
文摘Vehicle traveling time prediction is an important part of the research of intelligent transportation system. By now, there have been various kinds of methods for vehicle traveling time prediction. But few consider both aspects of time and space. In this paper, a vehicle traveling time prediction method based on grey theory （GT） and linear regression analysis （LRA） is presented. In aspects of time, we use the history data sequence of bus speed on a certain road to predict the future bus speed on that road by GT. And in aspects of space, we calculate the traffic affecting factors between various roads by LRA. Using these factors we can predict the vehicle＇s speed at the lower road if the vehicle＇s speed at the current road is known. Finally we use time factor and space factor as the weighting factors of the two results predicted by GT and LRA respectively to find the final result, thus calculating the vehicle＇s traveling time. The method also considers such factors as dwell time, thus making the prediction more accurate.
文摘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.
基金Foundation item: The National High Tech Research and Development Program(863) of China(No. 2002AA601140) and the National Natural Science Foundation of China(No. 50238020)
文摘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.
基金supported by National Key Basic Research Development Project (973) (N0.2003CB517103)
文摘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.
基金Supported by the National Natural Science Foundation of China(Grant No.10472006)
文摘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.
基金The authors are thankful to Director,NITK Surathkal and the Head of Applied Mechanics Department,NITK Surathkal for all the support and encouragement in the preparation of this paper.
文摘Breakwaters have been built throughout the centuries for the coastal protection and the port development,but changes occurred in their layout and criteria used for the design.Quarter circle breakwater(QBW)is a new type evolved having advantages of both caisson type and perforated type breakwaters.The present study extracts the effect of change in the percentage of perforations on the stable conditions of seaside perforated QBW by using various physical models.The results were graphically analyzed using dimensionless parameters and it was concluded that there is a reduction in dimensionless stability parameter with an increase in steepness of the wave and change in water depth to the height of breakwater structure.Multiple non–linear regression analysis was done and the equation for the best fit curve with a higher regression coefficient was obtained by using Excel statistical software—XLSTAT.
