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multiple regression analysis of risk factors related to radiation pneumonitis

World Journal of Clinical Cases 2023年第5期11卷 1040-1048页

作者： Ling-Ling Shi Jiang-Hua Yang Hong-Fa Yao Department of Radiology Huzhou Central HospitalAffiliated Central Hospital of Huzhou UniversityHuzhou 313000Zhejiang ProvinceChina

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 *** To carry out multiple regression analysis on the influencing factors of radiation *** 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 *** them,93 patients with radiation pneumonitis were included in the study group and 141 without radiation pneumonitis were included in the control *** characteristics,and radiation and imaging examination data of the two groups were collected and *** 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 *** 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(Pregression 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 *** We have identified patient age,type of lung cancer,history of chemotherapy,lung function,and radiotherapy pa

关键词： Radiation pneumonitis Influencing factors Radiotherapy multiple regression analysis

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Investigations on the relationship among the porosity,permeability and pore throat size of transition zone samples in carbonate reservoirs using multiple regression analysis,artificial neural network and adaptive neuro-fuzzy interface system

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Petroleum Research 2021年第4期6卷 321-332页

作者： Jamiu Oyekan Adegbite Hadi Belhaj Achinta Bera Petroleum Engineering Department Khalifa UniversityAbu DhabiUnited Arab Emirates Drilling Cementingand Stimulation Research CenterSchool of Petroleum TechnologyPandit Deendayal Energy UniversityGandhinagarGujarat382007India

Finding an accurate method for estimating permeability aside from well logs has been a difficult task for many *** most commonly used methods targeted towards regression technique to understand the correlation between pore throat radii,porosity and permeability are Winland and Pittman equation *** these methods are very common among petrophysicists,they do not give a good prediction in certain ***,this paper investigates the relationship among porosity,permeability,and pore throat radii using three methods such as multiple regression analysis,artificial neural network(ANN),and adaptive neuro-fuzzy inference system(ANFIS)for application in transition zone permeability ***,a comprehensive mercury injection capillary pressure(MICP)test was conducted using 228 transition zone carbonate core samples from a field located in the Middle-East *** regression analysis was later performed to estimate the permeability using pore throat and porosity *** the ANN,a two-layer feed-forward neural network with sigmoid hidden neurons and a linear output neuron was *** technique involves training,validation,and testing of input/output ***,for the ANFIS method,a hybrid optimization consisting of least-square and backpropagation gradient descent methods with a subtractive clustering technique was *** ANFIS combines both the artificial neural network and fuzzy logic inference system(FIS)for the training,validation,and testing of input/output *** results show that the best correlation for the multiple regression technique is achieved for pore throat radii with 35%mercury saturation(R35).However,for both the ANN and ANFIS techniques,pore throat radii with 55%mercury saturation(R55)gives the best *** the ANN and ANFIS are later found to be more effective and efficient and thus recommended as compared with the multiple regression technique commonly used in the industry.

关键词： multiple regression analysis Artificial neural network Adaptive neuro-fuzzy interface system Permeability and porosity Pore throat Mercury injection capillary pressure

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Research on the Effect of Artificial Intelligence Real Estate Forecasting Using multiple regression analysis and Artificial Neural Network: A Case Study of Ghana

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Journal of Computer and Communications 2021年第10期9卷 1-14页

作者： Madami Michael Ishaku Hill Isaac Lewu School of Computer Science and Engineering Anhui University of Science and Technology Huainan China

To transition from conventional to intelligent real estate, the real estate industry must enhance its embrace of disruptive technology. Even though the real estate auction market has grown in importance in the financial, economic, and investment sectors, few artificial intelligence-based research has tried to predict the auction values of real estate in the past. According to the objectives of this research, artificial intelligence and statistical methods will be used to create forecasting models for real estate auction prices. A multiple regression model and an artificial neural network are used in conjunction with one another to build the forecasting models. For the empirical study, the study utilizes data from Ghana apartment auctions from 2016 to 2020 to anticipate auction prices and evaluate the forecasting accuracy of the various models available at the time. Compared to the conventional multiple regression analysis, using artificial intelligence systems for real estate appraisal is becoming a more viable option (MRA). The Artificial Neural network model exhibits the most outstanding performance, and efficient zonal segmentation based on the auction evaluation price enhances the model’s prediction accuracy even more. There is a statistically significant difference between the two models when it comes to forecasting the values of real estate auctions.

关键词： Real Estate Forecasting Artificial Intelligence Artificial Neural Networks multiple regression analysis

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multiple regression analysis of Influencing Factors on Yield of New Sugarcane Variety Yuetang 03-373

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Asian Agricultural Research 2020年第5期12卷 47-49页

作者： Fangyin PAN Fuye LIU Mingfu WEN Qingwen LUO Guangdong Provincial Bioengineering Institute (Guangzhou Sugarcane Industry Research Institute)/Guangdong Key Lab of Sugarcane Improvement & Biorefinery Guangzhou 510316 China

[Objectives]The purpose of this study was to provide reference for cultivation and promotion of a new sugarcane variety Yuetang 03-373,on the basis of analyzing and summarizing the characters of the variety.[Methods]Correlation,multiple regression and path analyses were performed for the yield and yield components of Yuetang 03-373.[Results]Correlation analysis shows that cane yield was significantly correlated with millable stalk number,stalk length and stalk diameter,and among them,the correlation with millable stalk number was the *** regression and path analyses show that millable stalk number contributed the most to cane yield,followed by stalk length,and stalk diameter contributed the *** regression equation of cane yield against the three yield components was y=-2.8713+1.5497x1+5.8990x2-395.4294x3(R=0.9672**).[Conclusions]Millable stalk number and stalk length were the important and major factors for high yield of Yuetang 03-373,indicating that Yuetang 03-373 is a sugarcane variety of millable stalk *** cultivation,full play should be given to the advantage of Yuetang 03-373 in millable stalk number,as well as stalk length(plant height),in order to achieve the purpose of increasing yield.

关键词： Yuetang 03-373 Yield traits Correlation analysis multiple regression analysis

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Carbon stock and sink economic values of forest ecosystem in the forest industry region of Heilongjiang Province, China

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Journal of Forestry Research 2022年第3期33卷 875-882页

作者： Mingjuan Li Northeast Forestry University Harbin150040People’s Republic of China

The values of forest carbon stock (CSV) and carbon sink (COV) are important topics in the global carbon cycle. We quantitatively analyzed the factors affecting changes in both for forest ecosystem in 2000−2015. With multiple linear stepwise regression analysis, we obtained the factors that had a significant impact on changes of CSV and COV, and then the impacts of these variables on CSV and COV were used for further quantitative analysis using the vector autoregressive model. Our results indicated that both stand age and afforestation area positively affect CSV and COV;however, the forest enterprise gross output value negatively affects CSV. Stand age has the largest long-term cumulative impact on CSV and COV, reaching 40.4% and 9.8%, respectively. The impact of enterprise gross output value and afforestation area on CSV and COV is the smallest, reaching 4.0% and 0.3%, respectively.

关键词： Carbon stock value Carbon sink value multiple regression analysis VAR model

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Effects of land use, climate, topography and soil properties on regional soil organic carbon and total nitrogen in the Upstream Watershed of Miyun Reservoir, North China

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Journal of Environmental Sciences 2012年第3期24卷 387-395页

作者： Shufang Wang Xiaoke Wang Zhiyun Ouyang State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China

Soil organic carbon （SOC） and total nitrogen （TN） contents as well as their relationships with site characteristics are of profound importance in assessing current regional, continental and global soil C and N stocks and potentials for C sequestration and N conservation to offset anthropogenic emissions of greenhouse gases. This study investigated contents and distribution of SOC and TN under different land uses, and the quantitative relationships between SOC or TN and site characteristics in the Upstream Watershed of Miyun Reservoir, North China. Overall, both SOC and TN contents in natural secondary forests and grasslands were much higher than in plantations and croplands. Land use alone explained 37.2% and 38.4% of variations in SOC and TN contents, respectively. The optimal models for SOC and TN, achieved by multiple regression analysis combined with principal component analysis （PCA） to remove the multicollinearity among site variables, showed that elevation, slope, soil clay and water contents were the most significant factors controlling SOC and TN contents, jointly explaining 70.3% of SOC and 67.1% of TN contents variability. Only does additional 1.9% and 3% increase in the interpretations of SOC and TN contents variability respectively when land use was added to regressions, probably due to environment factors determine land use. Therefore, environmental variables were more important for SOC and TN variability than land use in the study area, and should be taken into consideration in properly evaluating effects of future land use changes on SOC and TN on a regional scale.

关键词： soil organic carbon soil total nitrogen principal component analysis multiple regression analysis

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Climatic envelope of evergreen sclerophyllous oaks and their present distribution in the eastern Himalaya and Hengduan Mountains

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Journal of Systematics and Evolution 2009年第3期47卷 183-190页

作者： 1,2Qing-Song YANG 1Wen-Yun CHEN 1,2Ke XIA 1Zhe-Kun ZHOU 1(Key Laboratory of Biodiversity and Biogeography, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China) 2(Graduate University of Chinese Academy of Sciences, Beijing 100049, China) (Key Laboratory of Biodiversity and Biogeography Kunming Institute of Botany Chinese Academy of Sciences Kunming 650204 China) (Graduate University of Chinese Academy of Sciences Beijing 100049 China)

Evergreen sclerophyllous oaks (the E.S. oaks, Quercus section Heterobalanus) are the dominant species of the local ecosystem in the eastern Himalaya and the Hengduan Mountains, southwest China. In this study, we document the climatic envelope of the seven E.S. oak species and examine the relationships between climate and their distribution. This was done using a principal components analysis (PCA) and multiple regression analysis (MRA) of nine climatic indices. The main climatic envelope of the E.S. oaks were: mean temperature of the warmest month (MTW)=12.0-19.5 ℃, warmth index (WI) = 33.2-88.9 ℃ month, annual biotemperature (BT)=-6.9--0.3 ℃, coldness index (CI)=-30.4- -10.1 ℃ month, mean temperature of the coldest month (MTC)=-3.7-3.0 ℃ and annual precipitation (AP)=701-897 mm at the lower limits; and MTW=8.3-16.1 ℃, WI=15.7-59.1 ℃ month, BT=3.6-8.9 ℃, CI=-55.4--19.3 ℃ month, MTC=8.3-16.1 ℃ and AP=610-811 mm at the upper limits. The climatic range of the E.S. oaks is wide and includes two climatic zones, the cool-temperature zone and the subpolar zone. The PCA and MRA results suggest that the thermal climate plays a major role and precipitation plays a secondary role in controlling the large-scale distribution of the E.S. oaks, except Quercus monimotricha. In thermal regimes, BT and/or MTW are most important for both lower and upper limits of the E.S. oaks. Furthermore, our results indicate that the upper distribution limits of the E.S. oaks are less determined by low temperatures and their duration (CI) than by other factors.

关键词： climatic indices distribution limits multiple regression analysis principal components analysis Quercus section Heterobalanus.

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Remote Detection of Hydrocarbon Microseepage in a Loess Covered Area

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Journal of Earth Science 2020年第1期31卷 207-214页

作者： Liang Zhao Darning Wang Shengbo Chen Lin Li Tianyu Zhang College of Geo-Exploration Science and Technology Jilin UniversityChangchun 130026China Division of Petroleum Geology China Geological SurveyBeijing 100037China Department of Earth Sciences Indiana University-Purdue University IndianapolisIndianapolis 46202USA College of Earth Science Jilin UniversityChangchun 130061China

Hydrocarbon microseepage can result in related near-surface mineral *** this study,we evaluated the potential of detecting these alterations with field measured and satellite acquired hyperspectral *** soil samples and reflectance spectra were collected in the Xifeng Oilfield,a loess covered *** samples were analyzed in the laboratory for calcite,dolomite,kaolinite,illite,and mixedlayer illite/smectite content,and we processed reflectance spectra for continuum removal to derive clay and carbonate mineral absorption depth(H).High correlation between absorption depth and mineral content was shown for clay and mineral carbonate with field measured *** on the result for the field spectra,we proposed and tested a fast index based on the absorption depth of clay and carbonate minerals with a hyperspectral image of the *** detected hydrocarbon microseepage anomalies matched well with those shown in the geological map.

关键词： hyperspectral remote sensing hydrocarbon microseepage spectrum absorption parameters multiple regression analysis fast index geochemistry

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Function of Palm Fiber in Stabilization of Alluvial Clayey Soil in Yangtze River Estuary

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Journal of Renewable Materials 2021年第4期9卷 767-787页

作者： Jili Qu Hao Zhu Department of Civil Engineering School of Environment and ArchitectureUniversity of Shanghai for Science and TechnologyShanghai200093China

Palm fiber is one of the favorable materials used in stabilization of soft soil in geotechnical engineering projects in recent years due to its nature of sustainability,no harm to the environment,biodegradability,availability and costeffectiveness in the context of widespread appeal from the world for returning to nature and protecting the earth our *** paper is aimed at exploring the mechanical performance of Shanghai clayey soil reinforced with palm *** unconfined compressive tests are carried out on samples treated with palm fibers of different lengths and contents,and the unconfined compressive strength(UCS),ductility rate(DR),secant modulus(SM),energy absorption capacity(EAC)and failure pattern(FP)of the reinforced and unreinforced samples have been analyzed with regard to their relationship with palm fiber contents and *** multiple regression,grey correlation and general correlation relationship analysis are applied to the resultant test data so as to obtain the mathematical and statistical equation of related soil *** has been concluded from the analysis that the unconfined compressive strength,ductility and energy absorption capacity of reinforced soil will increase with the increase in content and length of palm fiber,which are maximized when palm fiber content and length are 0.4%and 15 mm,*** the contrary,the secant modulus of reinforced soil decreases considerably with content and length of palm fiber as a ***,the failure pattern also changes from brittle to ductile gradually with the content and length of palm *** data provided by the analysis of reinforced soil can be referred to and used for the related geotechnical engineering in the *** the mathematical model obtained from the statistical regression is significantly meaningful because it can be used to predict the soil performance without the need for doing the additional tests,with saving in cost and ***’s more,the applic

关键词： Palm fiber Shanghai clayey soil UCS EAC multiple regression analysis

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Suggestion of advanced regression model on friction angle of fault gouge in South Korea

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Journal of Rock Mechanics and Geotechnical Engineering 2021年第6期13卷 1368-1379页

作者： Seong-Woo Moon Hyun-Seok Yun Yong-Seok Seo Department of Earth and Environmental Sciences Chungbuk National University1 Chungdae-roCheongju-siChungcheongbuk-do28644South Korea

Although friction characteristics of fault gouge are important to understand reactivation of fault,behavior of earthquake,and mechanism of slope failure,analysis results of fault gouge have low accuracy mostly than those of soils or rocks due to its high heterogeneity and low ***,to improve the accuracy of analysis results,we conducted simple regression analysis and structural equation model analysis and selected major influential factors of friction characteristics among many factors,and then we deduced advanced regression model with the highest coefficient of determination(R^(2)) via multiple regression *** most coefficients of determination in simple regression analysis are below0.3-0.4,coefficient of determination in multiple regression analysis is remarkably large as 0.657.

关键词： Fault gouge Friction angle Simple regression analysis Structural equation model analysis multiple regression analysis

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