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Application of cluster analysis and stepwise regression in predicting the traffic volume of lanes 被引量:5
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作者 张赫 王炜 顾怀中 《Journal of Southeast University(English Edition)》 EI CAS 2005年第3期359-362,共4页
Because of the difficulty to obtain the traffic flow information of lanes at non-detector intersections in most metropolises of the world,based on the relationships between the lanes of signal-controlled intersections... Because of the difficulty to obtain the traffic flow information of lanes at non-detector intersections in most metropolises of the world,based on the relationships between the lanes of signal-controlled intersections,cluster analysis and stepwise regression are integrated to predict the traffic volume of lanes at non-detector isolated controlled intersections.First cluster analysis is used to cluster the lanes of non-detector isolated signal-controlled intersections and the lanes of all signal-controlled intersections with detectors.Then, by the results of cluster analysis,the traffic volume samples are selected randomly and stepwise regression is used to predict the traffic volume of lanes at non-detector isolated signal-controlled intersections.The method is tested by the traffic volume data of lanes of the road network of Nanjing city.The problem of predicting the traffic volume of lanes at non-detector isolated signal-controlled intersections was resolved and can be widely used in urban traffic flow guidance and urban traffic control in cities without enough intersections equipped with detectors. 展开更多
关键词 intelligent transportation systems (ITS) cluster analysis stepwise regression
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Population Quantity Variations of Oriental Fruit Fly (Bactrocera dorsalis Hendel) on the Basis of Stepwise Regression Analysis
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作者 张丽莲 杨林楠 杨仕生 《Plant Diseases and Pests》 CAS 2010年第2期32-34,共3页
[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
关键词 Oriental fruit fly stepwise regression analysis Meteorological factors
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Model’s parameter sensitivity assessment and their impact on Urban Densification using regression analysis
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作者 Anasua Chakraborty Mitali Yeshwant Joshi +2 位作者 Ahmed Mustafa Mario Cools Jacques Teller 《Geography and Sustainability》 2025年第2期143-156,共14页
The impact of different global and local variables in urban development processes requires a systematic study to fully comprehend the underlying complexities in them.The interplay between such variables is crucial for... The impact of different global and local variables in urban development processes requires a systematic study to fully comprehend the underlying complexities in them.The interplay between such variables is crucial for modelling urban growth to closely reflects reality.Despite extensive research,ambiguity remains about how variations in these input variables influence urban densification.In this study,we conduct a global sensitivity analysis(SA)using a multinomial logistic regression(MNL)model to assess the model’s explanatory and predictive power.We examine the influence of global variables,including spatial resolution,neighborhood size,and density classes,under different input combinations at a provincial scale to understand their impact on densification.Additionally,we perform a stepwise regression to identify the significant explanatory variables that are important for understanding densification in the Brussels Metropolitan Area(BMA).Our results indicate that a finer spatial resolution of 50 m and 100 m,smaller neighborhood size of 5×5 and 3×3,and specific density classes—namely 3(non-built-up,low and high built-up)and 4(non-built-up,low,medium and high built-up)—optimally explain and predict urban densification.In line with the same,the stepwise regression reveals that models with a coarser resolution of 300 m lack significant variables,reflecting a lower explanatory power for densification.This approach aids in identifying optimal and significant global variables with higher explanatory power for understanding and predicting urban densification.Furthermore,these findings are reproducible in a global urban context,offering valuable insights for planners,modelers and geographers in managing future urban growth and minimizing modelling. 展开更多
关键词 Urban densification Sensitivity analysis Multinomial logistic regression stepwise regression
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An optimized protocol for stepwise optimization of real-time RT-PCR analysis 被引量:6
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作者 Fangzhou Zhao Nathan A.Maren +9 位作者 Pawel Z.Kosentka Ying-Yu Liao Hongyan Lu James R.Duduit Debao Huang Hamid Ashrafi Tuanjie Zhao Alejandra I.Huerta Thomas G.Ranney Wusheng Liu 《Horticulture Research》 SCIE 2021年第1期2474-2494,共21页
Computational tool-assisted primer design for real-time reverse transcription(RT)PCR(qPCR)analysis largely ignores the sequence similarities between sequences of homologous genes in a plant genome.It can lead to false... Computational tool-assisted primer design for real-time reverse transcription(RT)PCR(qPCR)analysis largely ignores the sequence similarities between sequences of homologous genes in a plant genome.It can lead to false confidence in the quality of the designed primers,which sometimes results in skipping the optimization steps for qPCR.However,the optimization of qPCR parameters plays an essential role in the efficiency,specificity,and sensitivity of each gene’s primers.Here,we proposed an optimized approach to sequentially optimizing primer sequences,annealing temperatures,primer concentrations,and cDNA concentration range for each reference(and target)gene.Our approach started with a sequence-specific primer design that should be based on the single-nucleotide polymorphisms(SNPs)present in all the homologous sequences for each of the reference(and target)genes under study.By combining the efficiency calibrated and standard curve methods with the 2−ΔΔCt method,the standard cDNA concentration curve with a logarithmic scale was obtained for each primer pair for each gene.As a result,an R 2≥0.9999 and the efficiency(E)=100±5% should be achieved for the best primer pair of each gene,which serve as the prerequisite for using the 2^(−ΔΔCt) method for data analysis.We applied our newly developed approach to identify the best reference genes in different tissues and at various inflorescence developmental stages of Tripidium ravennae,an ornamental and biomass grass,and validated their utility under varying abiotic stress conditions.We also applied this approach to test the expression stability of six reference genes in soybean under biotic stress treatment with Xanthomonas axonopodis pv.glycines(Xag).Thus,these case studies demonstrated the effectiveness of our optimized protocol for qPCR analysis. 展开更多
关键词 OPTIMIZATION analysis stepwise
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Multi-variate Stepwise Discriminant Analysis Research Affecting Portal Hypertension's Grade Factors of Liver Function 被引量:1
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作者 彭志海 覃修福 赵业民 《Journal of Huazhong University of Science and Technology(Medical Sciences)》 SCIE CAS 1994年第1期56-60,共5页
The idtal time for selecting portal hypertension operation is the accurate judgement of the grade of liver function.yet the present criterion in grading liver functicn is controversial.tco pztitnts vith 20 factoxs rel... The idtal time for selecting portal hypertension operation is the accurate judgement of the grade of liver function.yet the present criterion in grading liver functicn is controversial.tco pztitnts vith 20 factoxs related to poxttl hypeitersor wexe undergone stepwise discriminant analysis by using SAS software on the IBM/PC computer(significance levtl α=0.05).The results show that ascites degree prothrombin tmie(PT),serum total bilirubin,serum albumin content,main portal vein flow are significant fators.In the light of above variates contributing to grading liver function as to estblish a discriminant eqation,it was found that the total agreement rate between replaceable discimination and original Child-Pugh classification is 86%.A test for agieement was performed between discriminant and original classificaton,showing that the two kinds of classification methods have a good agreement rates (Kppa=0.7856),indicating the discriminant classification is of practica values. 展开更多
关键词 portal hypertension liver function classification multi-varate stepwise discrimnant analysis
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A quantitative analysis on the sources of dune sand in the Hulun Buir Sandy Land:application of stepwise discriminant analysis (SDA) to the granulometric data 被引量:1
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作者 HANGuang ZHANGGuifang YANGWenbin 《Journal of Geographical Sciences》 SCIE CSCD 2004年第2期177-186,共10页
Quantitatively determining the sources of dune sand is one of the problems necessarily and urgently to be solved in aeolian landforms and desertification research. Based on the granulometric data of sand materials fro... Quantitatively determining the sources of dune sand is one of the problems necessarily and urgently to be solved in aeolian landforms and desertification research. Based on the granulometric data of sand materials from the Hulun Buir Sandy Land, the paper employs the stepwise discriminant analysis technique (SDA) for two groups to select the principal factors determining the differences between surface loose sediments. The extent of similarity between two statistical populations can be described quantitatively by three factors such as the number of principal variables, Mahalanobis distance D 2 and confidence level 琢for F-test. Results reveal that: 1) Aeolian dune sand in the region mainly derives from Hailar Formation (Q 3 ), while fluvial sand and palaeosol also supply partially source sand for dunes; and 2) in the vicinity of Cuogang Town and west of the broad valley of the lower reaches of Hailar River, fluvial sand can naturally become principal supplier for dune sand. 展开更多
关键词 Hulun Buir Sandy Land granulometric analysis stepwise discriminant analysis dune sand Hailar Formation fluvial sandy sediments
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Analysis and Evaluation Indicator Selection of Chilling Tolerance of Different Cotton Genotypes 被引量:2
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作者 武辉 侯丽丽 +4 位作者 周艳飞 范志超 石俊毅 阿丽艳.肉孜 张巨松 《Agricultural Science & Technology》 CAS 2012年第11期2338-2346,共9页
[Objectivc] This study aimed to investigate the chilling tolerance of seedlings of different cotton genotypes and screen appropriate indicators for assess- ing chilling tolerance, to establish reliable mathematical ev... [Objectivc] This study aimed to investigate the chilling tolerance of seedlings of different cotton genotypes and screen appropriate indicators for assess- ing chilling tolerance, to establish reliable mathematical evaluation model for chilling tolerance of cotton, thus providing theoretical basis for breeding and promoting new chilling-tolerant cotton germplasms and large-scale evaluation of chilling tolerance of cotton varieties. [Method] Fifteen cotton varieties (lines) were used as experimental materials. The photosynthetic gas exchange parameters, chlorophyll fluorescence ki- netic parameters, chlorophyll content, relative soluble sugar content, malonaldehyde content, relative proiine content, relative conductivity and other 12 physiological indi- cators of seedling leaves under low temperature treatment (5 ℃, 12 h) and recovery treatment (25 ℃. 24 h) were determined; based on the chilling tolerance coefficient (CTC) of various individual indicators, the comprehensive evaluation of chilling toler- ance was conducled by using principal component analysis, hierarchical cluster anal- ysis and stepwise regression analysis. [Result] The results showed that the 12 indi- vidual physiological indicators could be classified into 7 independent comprehensive components by principal component analysis; 15 cotton varieties (lines) were clus- tered into three categories by using membership function method and hierarchical cluster analysis; the mathematical model for evaluating chilling tolerance of cotton seedlings was established: D =0.275 -0.244Fo1 +0.206Fv/Fm1+0.326g,%-0.056SS + 0.225MDA+O.O38REC (FF=0.995), and the evaluation accuracy of the equation was higher than 94.25%,0. Six identification indicators closely related to chilling tolerance were screened, including Fo,, Fv/Fm1, Seedling leaves of cotton varieties (lines) gs2, SS, MDA, and REC. [Conclusion] with high chilling tolerance are less dam- aged under low temperature stress, and are able to maintain relatively high photo- synthetic electron transport capacity and high stomatal conductance after recovery treatment, which is contributed to gas exchange and recovery of photosynthetic ca- pacity. Determination of the six indicators under the same stress condition can be adopted for rapid identification and prediction of the chilling tolerance of other cotton varieties, which provides basis for the breeding, promotion, identification and screen- ing of chilling tolerant germplasms. 展开更多
关键词 COTTON Chilling tolerance Principal components analysis Comprehensiveevaluation stepwise regression analysis
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Statistical Analysis of Leaf Water Use Efficiency and Physiology Traits of Winter Wheat Under Drought Condition 被引量:8
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作者 WU Xiao-li BAO Wei-kai 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2012年第1期82-89,共8页
Five statistical methods including simple correlation, multiple linear regression, stepwise regression, principal components, and path analysis were used to explore the relationship between leaf water use efficiency ... Five statistical methods including simple correlation, multiple linear regression, stepwise regression, principal components, and path analysis were used to explore the relationship between leaf water use efficiency (WUE) and physiological traits (photosynthesis rate, stomatal conductance, transpiration rate, intercellular CO2 concentration, etc.) of 29 wheat cultivars. The results showed that photosynthesis rate, stomatal conductance, and transpiration rate were the most important leaf WUE parameters under drought condition. Based on the results of statistical analyses, principal component analysis could be the most suitable method to ascertain the relationship between leaf WUE and relative physiological traits. It is reasonable to assume that high leaf WUE wheat could be obtained by selecting breeding materials with high photosynthesis rate, low transpiration rate, and stomatal conductance under dry area. 展开更多
关键词 leaf water use efficiency multiple linear regression path analysis principal components simple correlation stepwise regression wheat genotype
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Impacts of COVID-19 pandemic on urban park visitation:a global analysis 被引量:8
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作者 Dehui(Christina)Geng John Innes +1 位作者 Wanli Wu Guangyu Wang 《Journal of Forestry Research》 SCIE CAS CSCD 2021年第2期553-567,共15页
The COVID-19 pandemic has resulted in over 33 million confirmed cases and over 1 million deaths globally,as of 1 October 2020.During the lockdown and restrictions placed on public activities and gatherings,green space... The COVID-19 pandemic has resulted in over 33 million confirmed cases and over 1 million deaths globally,as of 1 October 2020.During the lockdown and restrictions placed on public activities and gatherings,green spaces have become one of the only sources of resilience amidst the coronavirus pandemic,in part because of their positive effects on psychological,physical and social cohesion and spiritual wellness.This study analyzes the impacts of COVID-19 and government response policies to the pandemic on park visitation at global,regional and national levels and assesses the importance of parks during this global pandemic.The data we collected primarily from Google’s Community Mobility Reports and the Oxford Coronavirus Government Response Tracker.The results for most countries included in the analysis show that park visitation has increased since February 16th,2020 compared to visitor numbers prior to the COVID-19 pandemic.Restrictions on social gathering,movement,and the closure of workplace and indoor recreational places,are correlated with more visits to parks.Stay-at-home restrictions and government stringency index are negatively associated with park visits at a global scale.Demand from residents for parks and outdoor green spaces has increased since the outbreak began,and highlights the important role and benefits provided by parks,especially urban and community parks,under the COVID-19 pandemic.We provide recommendations for park managers and other decision-makers in terms of park management and planning during health crises,as well as for park design and development.In particular,parks could be utilized during pandemics to increase the physical and mental health and social well-being of individuals. 展开更多
关键词 COVID-19 COVID-19 response policies Parks visitation stepwise regression analysis Urban parks
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乳腺癌术后患者自我形象的Stepwise多元回归分析调查 被引量:5
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作者 徐曼 贡树基 《护理实践与研究》 2020年第9期63-65,共3页
目的探讨乳腺癌术后患者自我形象水平的影响因素。方法选择我院2018年9月至2019年9月接收的70例乳腺癌术后患者以及同期70例健康女性作为研究对象,应用自我形象量表(BIBCQ)评分,分析乳腺癌术后患者自我形象的相关因素,并采用多元线性回... 目的探讨乳腺癌术后患者自我形象水平的影响因素。方法选择我院2018年9月至2019年9月接收的70例乳腺癌术后患者以及同期70例健康女性作为研究对象,应用自我形象量表(BIBCQ)评分,分析乳腺癌术后患者自我形象的相关因素,并采用多元线性回归分析,确定影响患者自我形象的独立因素。结果乳腺癌术后患者自我形象各维度评分明显高于健康女性(P<0.001),Stepwise多元线性回归分析显示,年龄、配偶态度、文化程度、抑郁焦虑是乳腺癌术后自我形象的独立影响因素。结论乳腺癌患者术后自我形象受配偶态度、年龄、文化程度等多种因素影响,临床应针对相关影响因素实施个性化护理服务。 展开更多
关键词 乳腺癌 自我形象 stepwise多元回归分析
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New empirical model to evaluate groundwater flow into circular tunnel using multiple regression analysis 被引量:6
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作者 Farhadian Hadi Katibeh Homayoon 《International Journal of Mining Science and Technology》 SCIE EI 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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Dam deformation analysis based on BPNN merging models 被引量:2
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作者 Jingui Zou Kien-Trinh Thi Bui +1 位作者 Yangxuan Xiao Chinh Van Doan 《Geo-Spatial Information Science》 SCIE CSCD 2018年第2期149-157,共9页
Hydropower has made a significant contribution to the economic development of Vietnam,thus it is important to monitor the safety of hydropower dams for the good of the country and the people.In this paper,dam horizont... Hydropower has made a significant contribution to the economic development of Vietnam,thus it is important to monitor the safety of hydropower dams for the good of the country and the people.In this paper,dam horizontal displacement is analyzed and then forecasted using three methods:the multi-regression model,the seasonal integrated auto-regressive moving average(SARIMA)model and the back-propagation neural network(BPNN)merging models.The monitoring data of the Hoa Binh Dam in Vietnam,including horizontal displacement,time,reservoir water level,and air temperature,are used for the experiments.The results indicate that all of these three methods can approximately describe the trend of dam deformation despite their different forecast accuracies.Hence,their short-term forecasts can provide valuable references for the dam safety. 展开更多
关键词 Dam deformation analysis multi-regression model Back-propagation Neural Network(BPNN) Seasonal Integrated Auto-regressive Moving Average(SARIMA)model merging model
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Influence Factors Analysis to Chlorophyll a of Spring Algal Bloom in Xiangxi Bay of Three Gorges Reservoir
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作者 Huajun LUO Defu LIU +2 位作者 Daobin JI Yuling HUANG Yingping HUANG 《Journal of Water Resource and Protection》 2009年第3期188-194,共7页
To study the relationship between environmental variables and chlorophyll a of spring algal bloom in Xiangxi Bay of Three Gorges Reservoir, stepwise multiple binomial regression and grey relative analysis methods were... To study the relationship between environmental variables and chlorophyll a of spring algal bloom in Xiangxi Bay of Three Gorges Reservoir, stepwise multiple binomial regression and grey relative analysis methods were adopted. In surveys, 13 stations have been investigated and 143 samples were collected weekly from March 4 to May 13 in 2007. The study shows environmental variables (turbidity, total nitrogen, dissolved oxygen, total phosphates and silicate) are key factors during algal bloom. The grey relative values and their permutation indicated that turbidity was the most important factor and had comprehensive effect on chlorophyll a. The more number of interactive variables is found to be an indication of biochemical activity during spring algal bloom in Xiangxi Bay such as DO×TN, Turb×TP and so on. There was good linear relationship between chlorophyll a and the interaction of DO with TN ( , ).The interac-tion of nutrients (TP×TN, TP×SiO4, TN×SiO4) had significant influence to chlorophyll a and probably determined the inter-specific competition at different nutrient concentrations. 展开更多
关键词 stepwise Multiple BINOMIAL Regression Grey Relative analysis CHLOROPHYLL a Environment Variables ALGAL BLOOM Xiangxi BAY
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金针菇单孢杂交后代丰产性预测指标筛选
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作者 陈珣 肇莹 +3 位作者 龚娜 刘国丽 马晓颖 肖军 《北方园艺》 北大核心 2025年第11期118-126,共9页
以35份金针菇单孢杂交后代为试材,采用相关性分析、逐步多元回归分析和通径分析方法,研究其纤维素酶、半纤维素酶、漆酶、菌柄直径、菌柄长度、菌盖宽度、菌盖厚度对产量的影响,以期提高金针菇杂交育种效率,快速筛选优质高产的金针菇单... 以35份金针菇单孢杂交后代为试材,采用相关性分析、逐步多元回归分析和通径分析方法,研究其纤维素酶、半纤维素酶、漆酶、菌柄直径、菌柄长度、菌盖宽度、菌盖厚度对产量的影响,以期提高金针菇杂交育种效率,快速筛选优质高产的金针菇单孢杂交后代。结果表明:菌柄长度、菌盖宽度、菌盖厚度与产量呈极显著正相关,菌柄直径、菌柄长度、菌盖宽度、菌盖厚度各性状之间均存在极显著正相关,与通径分析结果一致,菌盖厚度对产量的直接作用最大,菌柄长度通过菌盖厚度对产量的间接作用最大。通过逐步回归分析得到以漆酶活性(X_(3))、菌柄长度(X_(5))、菌盖厚度(X_(7))为三要素的金针菇单孢杂交后代产量的最优回归模型Y=-0.244X_(3)+0.400X_(5)+0.483X_(7)。因此确定菌丝体漆酶活性、菌盖厚度、菌柄长度作为金针菇单孢杂交后代丰产性预测指标。 展开更多
关键词 金针菇 单孢杂交 相关性分析 逐步多元回归分析 通径分析
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高校知识服务赋能机理与仿真试验
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作者 陈旭华 潘星宇 《福州大学学报(自然科学版)》 北大核心 2025年第3期261-268,共8页
采用混合研究方法,对308份有效样本数据进行定量分析,通过逐步回归分析筛选出具有统计学意义的赋能变量以及其对知识服务效能的影响程度.在此基础上,运用系统动力学方法进行系统建模和仿真试验.结果表明,组织、知识、制度、心理及市场... 采用混合研究方法,对308份有效样本数据进行定量分析,通过逐步回归分析筛选出具有统计学意义的赋能变量以及其对知识服务效能的影响程度.在此基础上,运用系统动力学方法进行系统建模和仿真试验.结果表明,组织、知识、制度、心理及市场赋能对知识服务效能产生正向影响,系统动力学模型能够较好地模拟赋能视角下知识服务过程的演变.在知识服务初期,服务效能受到赋能影响不显著.中后期,各赋能维度对服务效能影响显著,知识创新与传递加快,其中,组织赋能影响最显著,但多维赋能的综合效用优于单一维度赋能. 展开更多
关键词 知识服务 赋能 逐步回归分析 系统动力学 仿真分析
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数据挖掘下车险续保概率及画像建模研究
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作者 秦雅琴 梁璐 +1 位作者 许庚 周燕宁 《重庆理工大学学报(社会科学)》 2025年第3期145-156,共12页
以我国车辆保险为主要研究对象,为续保概率模型及车险用户精准画像建模。通过主成分分析法提取8个主要成分,运用逐步回归模型对车险续保率与多个影响因素间的关系进行实证优化研究,建立续保概率模型,并利用支持向量机二元分类模型进行... 以我国车辆保险为主要研究对象,为续保概率模型及车险用户精准画像建模。通过主成分分析法提取8个主要成分,运用逐步回归模型对车险续保率与多个影响因素间的关系进行实证优化研究,建立续保概率模型,并利用支持向量机二元分类模型进行预测。为研究车险用户的画像建模,运用二阶聚类算法做出车险用户的精准画像。结果显示:建立的续保概率模型,准确率高达92.8%;车险续保用户具体分为3类。利用所建立的模型和统计结果,从影响客户决策的因素进行判断分析,并从财险企业的管理经营角度提出相应改善建议和优惠政策,以提高客户的续保概率。为车险用户精准画像可起到风险管控的作用,减少交通事故,管理社会冲突,维护社会秩序。 展开更多
关键词 主成分分析 逐步回归 PCA-SVM 二阶聚类 画像建模
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小麦直立株型种质耐密性评价及鉴定指标筛选 被引量:3
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作者 刘梦莹 张玉 +5 位作者 张嘉豪 陈建省 张卫东 孟庆福 马玉华 鄢照新 《麦类作物学报》 北大核心 2025年第3期349-359,共11页
作为一种特殊株型,小麦直立株型的特点是分蘖直立生长,冠层紧密,常规行距种植行间空隙大,而且直立株型小麦冠层穗容量较大,如果增加播量,缩减行距,可提高小麦产量。因此,有必要研究直立株型小麦在密植条件下的性状表现。本研究以15个不... 作为一种特殊株型,小麦直立株型的特点是分蘖直立生长,冠层紧密,常规行距种植行间空隙大,而且直立株型小麦冠层穗容量较大,如果增加播量,缩减行距,可提高小麦产量。因此,有必要研究直立株型小麦在密植条件下的性状表现。本研究以15个不同亲本来源的直立株型小麦品系为材料,在高密度(3.30×10^(6)株·hm^(-2))、超高密度(4.50×10^(6)株·hm^(-2))下种植,调查了9个主要农艺性状;计算性状耐密系数,通过主成分分析进行指标转化,计算综合耐密评价值(D值);利用逐步回归分析方法建立数学模型,筛选适合的耐密鉴定指标。结果表明,在适当高密条件下,直立株型小麦可以获得较高的籽粒产量;3个综合指标的累计贡献率为85.24%,依据D值聚类分析可将15个材料分为极强、强、中度和弱耐密型小麦;其中6个性状,包括鲜重(X_(7))、千粒重(X_(4))、倒伏程度(X_(9))、单位面积穗数(X_(2))、株高(X_(5))和机械强度(X_(8)),可作为小麦直立株型品系的耐密性鉴定的核心指标,耐密性评估数学模型为D=4.330X_(7)+8.838X_(4)-0.325X_(9)+0.463X_(2)+4.501X_(5)+2.092X_(8)-18.499,估计精度在89.20%以上。 展开更多
关键词 小麦 耐密性 主成分分析 隶属函数法 逐步回归
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不同苦荞种质资源耐荫性评价及鉴定指标的筛选 被引量:1
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作者 张鲜 赵少迪 +5 位作者 胡传伟 吴晓梅 王秋宝 刘月贤 田洪岭 张丽君 《核农学报》 CAS 北大核心 2025年第2期223-232,I0001-I0004,共14页
为建立耐荫性评价模型以筛选苦荞耐荫种质资源,以60份苦荞种质资源为材料,采用田间试验,设置遮荫和自然光两种处理,测定株高等9个形态结构指标和超氧化物歧化酶(SOD)活性等6个生理指标,计算各指标的耐荫系数。采用多元统计分析方法对苦... 为建立耐荫性评价模型以筛选苦荞耐荫种质资源,以60份苦荞种质资源为材料,采用田间试验,设置遮荫和自然光两种处理,测定株高等9个形态结构指标和超氧化物歧化酶(SOD)活性等6个生理指标,计算各指标的耐荫系数。采用多元统计分析方法对苦荞耐荫性进行综合评价及耐荫指标的筛选。结果表明,15个指标的耐荫系数存在不同程度的变异,变异系数范围为7.87%~85.84%,除丙二醛(MDA)含量、过氧化物酶(POD)和过氧化氢酶(CAT)活性外,其他各单项指标间均存在一定的相关性。通过主成分分析,从15个指标的耐荫系数中提取了5个主成分,其累计方差贡献率达69.307%。利用隶属函数分析法计算60份苦荞种质资源的综合评价值(D),并在此基础上采用聚类分析将种质资源分为耐荫型、中度耐荫型和敏感型3类。进一步利用逐步回归分析建立最优线性回归方程D=-0.176+0.115X_(1)+0.313X_(5)+0.140X_(6)+0.057X_(7)+0.176X_(10)-0.015X_(13),筛选出株高、主茎粗第五节、主茎粗第八节、单株粒数、始花期叶绿素相对含量(SPAD)、POD活性共6个耐荫性鉴定指标。本研究结果为苦荞耐荫抗倒伏种质资源鉴定及新品种选育提供了参考依据。 展开更多
关键词 苦荞 耐荫性评价 主成分分析 聚类分析 逐步回归分析
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利用小波分解重构GRACE地下水储量成分研究 被引量:1
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作者 张勇刚 王正涛 +1 位作者 高瑀 田坤俊 《武汉大学学报(信息科学版)》 北大核心 2025年第1期20-29,共10页
重力恢复与气候实验(gravity recovery and climate experiment,GRACE)数据解算出的时变重力场模型为陆地水储量的研究提供了一种全新的途径,然而,GRACE数据只能解算出格网点分辨率上总体的水储量变化,包括地表水、土壤水、地下水和植... 重力恢复与气候实验(gravity recovery and climate experiment,GRACE)数据解算出的时变重力场模型为陆地水储量的研究提供了一种全新的途径,然而,GRACE数据只能解算出格网点分辨率上总体的水储量变化,包括地表水、土壤水、地下水和植被水等,却无法分离垂直层面上不同深度的水储量成分。采用小波分解方法,将扣除全球陆地数据同化系统水文模型地表水成分的GRACE信号进行分解,利用分解得到的小波子函数结合美国区域内的水井实测数据对地下水成分进行回归分析,并通过二维曲面插值的方法得到全美地区不同小波子函数的回归系数,以此来重构长时间连续的地下水储量变化序列。结果表明,在测试点位中61.84%以上的点位其相关系数达到0.4以上,62.90%的点位其均方根值在1.0 m以下,此方法可以得到地下水时空分布特征,为地下水资源的利用与研究提供数据支撑。 展开更多
关键词 GRACE卫星 小波分析 逐步回归 地下水储量
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