Predicting urbanization level by main element analysis and multiple linear regression---taking Xiantao district in Hubei Province as an example

In this paper we firstly select main factors relating to urbanization level of Xiantao District in Hubei Province by main element, then, make model of urbanization level by analysis of multiple liner regression, and lastly predict its urbanization level

Correlation Analysis of Fiscal Revenue and Housing Sales Price Based on Multiple Linear Regression Model

This paper selects seven indicators of financial revenue and housing sales price in recent 19 years in China,and uses SPSS and Excel to carry out descriptive statistics,independent sample t-test,correlation analysis and regression analysis to comprehensively study the correlation between financial revenue and housing sales price in China,and establishes the relationship between financial revenue and housing sales price When the average selling price of commercial housing increases by one unit,the fiscal revenue will increase by 27.855 points.

Regression analysis and its application to oil and gas exploration:A case study of hydrocarbon loss recovery and porosity prediction,China

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.

Design and Analysis of a Power Efficient Linearly Tunable Cross-Coupled Transconductor Having Separate Bias Control

A common current source, generally used to bias cross-coupled differential amplifiers in a transconductor, controls third harmonic distortion (HD3) poorly. Separate current sources are shown to provide better control on HD3) . In this paper, a detailed design and analysis is presented for a transconductor made using this biasing technique. The transconductor, in addition, is made to offer high Gm, low power dissipation and is designed for linearly tunable Gm with current mode load as one of the applications. The circuit exhibits HD3) of less than –43.7 dB, high current efficiency of 1.18 V-1 and Gm of 390 μS at 1 VGp-p @ 50 MHz. UMC 0.18 μm CMOS process technology is used for simulation at supply voltage of 1.8 V.

Statistical Analysis of Leaf Water Use Efficiency and Physiology Traits of Winter Wheat Under Drought Condition

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.

Biomass estimation of Shorea robusta with principal component analysis of satellite data

Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.

Study on mechanism and genetic analysis of lipid metabolism disorder in pregnant rats

Objective: To analyze the characteristics and possible mechanism of lipid metabolism in pregnant rats with intestinal flora imbalance. Methods: A total of 129 sexually mature female SD rats were divided into three groups: non-pregnant group (untreated healthy rats), healthy pregnant group (natural insemination pregnant rats), and pregnant microflora disorder group (pregnant rats were given mixed antibiotics by gavage to build the modeling), with 43 rats in each group. The contents of TG, LDL, HDL and TC were detected by automatic biochemical analyzer, and the contents of SCD1, PGC-1 alpha, PEPCK, ApoE and MTTP genes were detected by fluorescence quantitative PCR technology. Regression analysis was used to explore the comprehensive influence of each gene on total cholesterol expression in rats. Principal component analysis was used to explore the internal mechanism of lipid metabolism in pregnant rats with intestinal flora disorder. Results: The contents of TG, TC, LDL and HDL were compared among the three groups of rats and the differences were statistically significant (P<0.05) . The expression levels of related genes (SCD1, PGC-1, PEPCK, ApoE, MTTP) in the three groups were statistically significant (P<0.05) . SCD1 content in the non-pregnant group, healthy pregnancy group, and disordered pregnancy group was (0.92±0.12) μg/mL, (1.20±0.15)μg/mL, and (1.53±0.20) μg/mL, respectively. PGC-1 alpha content in the non-pregnant group, healthy pregnancy group, and disordered pregnancy group was (1.34±0.21) μg/mL, (0.93±0.12) micron /mL, and (0.41±0.08) μg/mL, respectively. PEPCK content in the non-pregnant group, healthy pregnancy group, and disordered pregnancy group was (0.48±0.06) μg/mL, (0.35±0.09)μg/mL, and (0.22±0.05) μg/mL, and the differences were statistically significant (P<0.05) . Multivariate linear regression analysis showed that the influence of gene content on The effect of each gene content on TC content was in order from large to small: SCD1 (OR=4.572) , PGC-1 (OR=3.387) , PEPCK (OR=3.935) , ApoE (OR=3.597) , MTTP (OR=3.096) . The principal component analysis showed that three principal components could be extracted from five related genes of lipid metabolism in pregnant rats with intestinal dysbiosis: SCD1/PEPCK pathway (contribution rate: 36.28%) , PGC-1 /ApoE pathway (contribution rate: 30.42%) , and MTTP pathway (contribution rate: 15.37%) . Conclusion: After pregnancy, blood lipids in rats are significantly increased while the imbalance of intestinal flora will lead to decreased blood lipids. The disorder of lipid metabolism in pregnant rats with intestinal flora imbalance is mainly related to the disorder of gene expression, which further affects the functions of SCD1/PEPCK, PGC-1 /ApoE and MTTP pathways.

Education Investment Fixed Asset Investment and Regional Economic Development Differences--Empirical analysis based on Chinese

In this article,it discusses the di£ferences in economic development between urban and rural areas and regions in our country from the perspective of education investment and fixed asset investment.Based on the provincial data of 31 provinces from 1999 to 2017 released by National Bureau of Statistics,it expends the Cobb-Douglas model and Lucas model,and analyses the data with multiple linear regression models.From the study,it finds that compared with investment in fixed assets,investment in education has a larger role in promoting economic development,which is more obvious in the underdeveloped central and western regions and rural areas.However,at the same time it needs to note that the positive effects of education investment will be restricted by the economic structure and policy environment,and education expenditure policies should also be implemented in accordance with time and local conditions.

Analysis and Evaluation of Housing Price Factors Using Mathematical Modeling

In recent years,the real estate industry has achieved significant progress,driving the development of related sectors and playing a crucial role in economic growth.However,rapid real estate market expansion has led to challenges,particularly concerning housing prices,which have drawn widespread societal attention.This article explores the theories of housing prices,analyzes factors influencing them,and conducts an empirical investigation of the impact of representative factors on ordinary residential prices.Using regression analysis and the entropy weight method,a mathematical model was developed to examine how various factors affect housing prices.

疫情后深圳市生活垃圾产生量的预测及变化分析

疫情后针对生活垃圾产生量的变化,开展预测并对结果进行分析,是地方政府科学制定相关规划、合理布局环卫设施建设的重要依据。因此,立足深圳市疫情前后数据,结合灰色关联度模型、多元线性回归等方法,分析2022—2035年生活垃圾产生量预测值的变化。结果表明,生活垃圾产生量保持逐年增长趋势,规划期末水平年(2035年)的具体数值有一定程度调整。预测到2035年的生活垃圾产生量为45 547 t/d,其中再生资源回收量为14 576 t/d,生活垃圾处理处置量为30 971 t/d。建议各项环卫设施建设可灵活调整设施规模及建设周期,提升城市垃圾处理效能。

浸矿作用下离子型稀土典型重金属释放规律研究

浸矿场地土壤重金属污染严重制约离子型稀土资源绿色开发。在原地浸矿过程中,浸矿液与稀土阳离子发生离子交换反应,同时置换出部分重金属离子,导致土壤重金属活化,进而造成土壤及地下水重金属污染。通过开展不同浓度MgSO_(4)浸矿条件下离子型稀土模拟浸矿试验,揭示了浸矿液浓度对离子型稀土重金属Cu、Zn、Pb和Tl释放的影响规律,通过相关性分析和多元线性回归分析,对重金属含量与影响因素进行解析。研究结果表明:在不同浓度MgSO_(4)的浸矿作用下,典型重金属呈现纵向迁移的趋势。重金属Cu、Pb、Tl含量与MgSO_(4)浓度之间存在负相关关系,Zn含量与MgSO_(4)浓度相关性不显著,Cu主要富集在中层土壤,Zn主要富集在中下层土壤,Pb和Tl主要富集在下层土壤。土壤pH值与Eh值呈显著负相关,土壤pH值、Eh值与典型重金属存在相关性。研究结果为矿区土壤重金属污染防治与绿色开采提供理论依据。

基于正交试验的煤岩相似材料最优配比研究

目的为了探寻煤岩相似材料最优配比,方法以赵固一矿煤样的自然视密度、单轴抗压强度、弹性模量为模拟指标,采用正交设计法开展相似材料配比试验。选用碳酸钙、水泥、细河砂、煤粉、蒸馏水为原料,以骨料与胶结剂质量比、胶结剂成分间质量比、骨料成分间质量比和掺水率为控制因素,按照4因素3水平正交配比方案制备了9组相似材料。结果试验结果表明:不同配比下相似材料物理力学参数变化较大,各因素对模拟指标影响规律性强,且骨胶比对相似材料各模拟指标起控制作用,自然视密度、单轴抗压强度、弹性模量均随骨胶比增加而显著下降。通过多元线性回归分析得到相似材料最优配比为碳酸钙∶水泥∶河砂∶煤粉∶水=1∶4∶0.9∶5.8∶3.3,经验证,使用该配比制作的试样在物理力学参数、单轴压缩曲线和破坏形态上能够很好地模拟原煤。结论该研究采用理论与试验相结合的方法寻找最优配比有效可行,可为煤岩相似材料领域研究提供一定借鉴。

秦岭北麓乡村植物景观与物种丰富度的关系

选取陕西省秦岭北麓5个村落作为试验区,采用多元线性回归分析和熵值法等相结合,探讨了秦岭北麓乡村地区植物丰富度对乡村景观的影响。结果表明:远离城镇的乡村植物多样性单一,物质丰富度偏低,其乡村景观评价指标体系得分偏低。多元线性逐步回归分析结果表明,Pielou均匀度指数与社会效应、美感效果、生态质量之间存在显著正相关,Menhinick丰富度指数与美感效果、生态质量、文化价值之间存在显著正相关。综上,提出了在乡村景观建设过程中,应立足资源优势,选择适合乡村景观发展的优势特色植物,有效增加评价较低乡村近水生境、居民点周边、农田边缘、林地比例和物种丰富度等建议,以期在促进乡村可持续发展的同时维护农村的环境治理,为乡村景观建设中植物多样性研究提供参考。

渤海海域井壁取心裂解烃S_(2)烃类损失恢复回归分析

地化录井受工程、地质条件及人为因素的影响,往往造成岩石样品从井底到地表的烃类损失,不能很好地反映地下储层的真实含油气信息,因此需要一种合理准确的方法进行烃类损失恢复。针对渤海海域不同地区不同层位的岩屑值(自变量)与壁心值(因变量)之间的关系,基于最小二乘法、梯度下降法及其衍生算法,以多元线性回归和非线性回归两种方式来拟合研究区井壁取心数据。多元线性回归模型可使用标准方程法、岭回归、LASSO(Least Absolute Shrinkage and Selection Operator)及弹性网进行回归拟合,非线性回归模型可使用梯度下降法和分段函数的拟合方法。对不同回归分析方法进行分析对比可知,岭回归在计算线性关系的烃类损失方面具有较好的效果,决定系数r^(2)均超过0.7;基于岭回归分段函数拟合和非线性回归模型y=x/(b+kx)适合非线性烃类损失恢复。与传统的烃类损失恢复方法相比,使用量化的方式对研究区烃类进行恢复,更加科学全面,具有广泛的应用前景。

武都地区初榨橄榄油酚类和脂肪酸组成对油脂氧化稳定性研究

对武都地区的白橄榄(U)、恩帕特雷(E)、奇迹(K)、阿斯(As)、中山24(Z)、云台14(Y)、皮瓜尔(P)、豆果(Arbe)、小苹果(M)、鄂植8(Ez)、阿尔伯萨拉(Arbo)、科拉蒂(C)、莱星(L)、佛奥(F)这14个品种初榨橄榄油的脂肪酸、酚类成分及油脂氧化稳定性进行检测和分析,单因素方差分析表明:品种间多酚和脂肪酸含量及油脂氧化稳定性存在显著性差异(p<0.05)。所有分析样品的脂肪酸组成均符合欧盟特级初榨橄榄油标准,初榨橄榄油中油酸质量分数在(56.12±0.24)%(豆果)和(71.45±0.42)%(科拉蒂)之间,亚油酸质量分数在(5.73±0.06)%(皮瓜尔)和(15.80±0.05)%(阿斯)之间,棕榈酸质量分数在(12.67±0.12)%(科拉蒂)和(18.76±0.04)%(豆果)之间。裂环烯醚萜类是主要的酚类成分,总酚质量分数最高为奇迹,为(471.35±29.34)mg/kg,最低为豆果,仅(165.65±8.08)mg/kg。主成分分析表明:富含橄榄苦苷苷元、女贞子苷元、橄榄裂环烯醚萜、油酸、芹菜素的品种氧化稳定性越高,而富含棕榈酸、亚油酸、酪醇、羟基酪醇、刺激醛的品种氧化稳定性越低。基于芹菜素、橄榄裂环烯醚萜、木犀草素和亚油酸建立的多元线性逐步回归模型可以预测90.70%的油脂氧化稳定性变化(p<0.001)。

高山地区夏季大气PM_(2.5)中元素的污染特征、生态风险及健康风险评估——以武当山为例

为了解华中高山地区夏季大气PM_(2.5)中元素的污染特征,于2018年6月在湖北省十堰市武当山国家空气质量监测站采集PM_(2.5)样品,利用电感耦合等离子体质谱仪(ICP-MS)测定样品中18种元素(Na、K、Ca、Mg、Al、Fe、V、Cr、Mo、Cu、Zn、Mn、Ni、As、Se、Cd、Ba和Pb)的浓度,并探讨了其来源、生态风险和健康风险.结果表明,武当山PM_(2.5)的日均浓度范围为5.00—33.65μg·m^(-3),平均浓度为(16.84±7.07)μg·m^(-3);元素K、Na、Fe、Ca、Al、Mg和Zn的浓度较高,7种元素占所分析元素的97.68%以上;富集因子结果表明,Mo、Zn、Pb、Cd和Se的EF值高于100,可能受周边人为活动排放污染物的区域或长距离传输影响;主成分-多元线性回归(PCA-MLR)结果表明,PM_(2.5)中元素主要来自于燃煤和机动车(57.57%)、工业源(22.52%)和地壳(19.91%);武当山PM_(2.5)重金属的生态风险指数极高,其中Cd、Se和Mo的潜在生态危害程度极强;健康风险评估显示,综合非致癌风险(HI)在儿童和成人中分别为2.28×10-2和3.04×10-2,均在可接受水平内,综合致癌风险(CRT)在儿童和成人中分别为4.45×10-7和2.37×10-6,说明成人存在潜在的致癌风险;Cr在成人中的致癌风险为1.88×10-6,说明Cr在成人中存在潜在的致癌风险,同种金属对人体的非致癌风险和致癌风险均表现为成人>儿童.

北京典型汇水区域雨水径流温度特征及影响因素分析

城市化发展导致不透水地表面积率大幅攀升,由此带来的一系列问题逐渐受到人们关注,夏季城市汇水区域地表产生高温径流后汇入下游受纳水体所造成的雨水径流热污染,对水生态、水环境造成不良影响的风险尤为突出。选取北京市典型汇水区域,对2021—2022年多场降雨径流出流温度进行监测与分析,并对气象因素、下垫面温度及管道内径流热量等数据进行同步采集,运用皮尔逊相关系数法分析其影响因素。结果表明:研究区域夏季降雨常出现雨水径流温度升高现象,降水量小于12.5mm、降雨历时短于250 min的降雨场次更易于升温,升温幅度最高可达4.1℃;径流温度升高往往出现在径流过程初期,温度达峰平均时间为38 min;径流是否升温与降雨强度峰值位置之间没有明显关系;气温、不透水地表初始时刻温度、降雨历时及降水量是雨水径流温度的极显著影响因素(P<0.01);降雨期间气温、降雨历时、不透水地表初始时刻温度和管道内壁温度4个指标,可以基本解释研究区域96.7%的径流温度输出情况。

结合多特征与线性判别分析的图像检索

卷积神经网络的全连接层特征缺乏对图像底层信息的描述,导致部分样本无法被成功检索。并且全连接层特征维度高,检索效率低下。针对这种情况,提出一种结合线性判别分析和多层特征的图像检索方法。该方法利用卷积神经网络提取卷积层和全连接层特征,并融合HSV特征,使用线性判别分析对融合特征降维。多层特征能增加图像的区分度,提升识别准确率。与其他算法的实验结果表明,该方法在检索精度和检索速度上有一定的提高。

湖北省温州蜜柑果实化渣性分析与评价

【目的】探究湖北省温州蜜柑果实的化渣性差异及其主要影响因素,为温州蜜柑高品质栽培提供理论基础。【方法】通过感官评价、质构仪检测对温州蜜柑化渣性进行综合评价,并通过相关性分析及多元线性回归分析初步解析温州蜜柑果实化渣性的主要影响因素。【结果】果实横径、纵径、单果质量与剪切力、木质素含量呈显著正相关;化渣度得分与可滴定酸(TA)含量、剪切力、穿刺力呈显著负相关,而剪切力与穿刺力呈显著正相关;木质素含量与果皮厚度和剪切力呈显著正相关,与固酸比(SAR)呈显著负相关;果胶含量与横径、TA、纤维素含量呈显著正相关。利用多元线性回归分析构建了包括可溶性固形物(TSS)含量、穿刺力、木质素含量和果胶含量4个指标且具有统计学意义的感官综合评价的预测模型:Y(化渣度得分)=5.875+0.108×X(TSS)-0.007×X(穿刺力)-0.007×X(木质素含量)+0.044×X(果胶含量)。模型综合口感预测得分与综合口感实际得分基本一致。【结论】基于回归分析建立的综合得分预测模型可实现温州蜜柑果实感官品质的综合评价,质构特征指标和理化成分指标作为客观方法可以较好地弥补感官分析的主观性缺陷,可应用于湖北省温州蜜柑的化渣性评价。

基于多元线性回归与决策树模型的病种费用分析——以儿童支气管肺炎为例

目的对儿童支气管肺炎住院费用分组,旨在DIP付费下,为住院费用的控制提出更合理的建议。方法通过统计软件SPSS 22对某三甲医院2019—2022年10月3448名儿童支气管肺炎出院患者,进行单因素分析和多元线性回归分析,结果筛选出分节点变量,用决策树模型对费用进行组合,并制定各组标准住院费用与权重。结果该院儿童支气管肺炎住院费用逐年上升,但费用结构却在优化。通过多元线性回归分析,将平均住院日、入院病况与年龄三个显著性因素作为分类节点,使用决策树模型,共分为6个费用组,并提出各组费用控制标准与预警上线。结论通过住院费用的预测值与费用预警线能够为支气管肺炎费用管理提供更为精准的参考与建议,节约卫生资源。