Reliability Distribution of Numerical Control Lathe Based on Correlation Analysis

Combined Reliability distribution with correlation analysis,a new method has been proposed to make Reliability distribution where considering the elements about structure correlation and failure correlation of subsystems.Firstly,we make a sequence for subsystems by means of TOPSIS which comprehends the considerations of Reliability allocation,and introducing a Copula connecting function to set up a distribution model based on structure correlation,failure correlation and target correlation,and then acquiring reliability target area of all subsystems by Matlab.In this method,not only the traditional distribution considerations are concerned,but also correlation influences are involved,to achieve supplementing information and optimizing distribution.

Analysis of Factors Influencing Comprehensive Productivity of Agriculture in Henan Province on the Basis of Grey Correlation

According to the data from Henan Statistical Yearbook from 2002 to 2008, from production capital, production conditions, labour inputs and financial support, this paper selects 11 variables influencing comprehensive productivity of agriculture in Henan Province. Through calculation and analysis of grey correlation of variables and comprehensive productivity of agriculture, this paper determines the impact of different variables on comprehensive productivity of agriculture. The results show that the agricultural capital has become the most important factor influencing comprehensive productivity of agriculture in Henan Province, while the impact of production conditions, labour inputs and financial support on comprehensive productivity of agriculture in Henan Province diminishes in turn. Corresponding countermeasures and suggestions are put forward to promote the sustainable development of comprehensive productivity of agriculture in Henan Province as follows: strengthen agricultural financial system building, and ensure agricultural production expenditure; scientifically arrange allocation of agricultural resources, and improve agricultural production conditions; carry out training of agricultural skills, and elevate the quality of agricultural labour forces; increase financial expenditure for agricultural production, and optimize financial expenditure structure.

Correlations between direct and indirect strength test methods

The difficulties associated with performing direct compression strength tests on rocks lead to the development of indirect test methods for the rock strength assessment. Indirect test methods are simple, more economical, less time-consuming, and easily adaptable to the field. The main aim of this study was to derive correlations between direct and indirect test methods for basalt and rhyolite rock types from Carlin trend deposits in Nevada. In the destructive methods, point load index, block punch index, and splitting tensile strength tests are performed. In the non-destructive methods, Schmidt hammer and ultrasonic pulse velocity tests are performed. Correlations between the direct and indirect compression strength tests are developed using linear and nonlinear regression analysis methods. The results show that the splitting tensile strength has the best correlation with the uniaxial compression strength.Furthermore, the Poisson's ratio has no correlation with any of the direct and indirect test results.

A precise tidal prediction mechanism based on the combination of harmonic analysis and adaptive network-based fuzzy inference system model

An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.

Analysis of the Influence Factors of Grain Supply-Demand Gap in China

Based on the analysis of the grain supply and demand gap’s current situation in China, this paper establishes an indicator system for the influence factors of grain supply and demand gap. Then this paper calculates the correlation degree between the main grain varieties’ supply and demand gap and its influence factors. The results show that sown area and unit yield have the greatest impact on wheat supply and demand gap;per capita disposable income and unit yield have the greatest impact on corn supply and demand gap;per capita disposable income and agricultural mechanization level have the greatest impact on the supply and demand gap of soybean and rice. From the analysis results, we can obtain the difference between the factors affecting the grain supply and demand gap, and provide a certain theoretical basis and new ideas for the balance of grain supply and demand in China.

MODAL PARAMETERS EXTRACTION WITH CROSS CORRELATION FUNCTION AND CROSS POWER SPECTRUM UNDER UNKNOWN EXCITATION

In most of real operational conditions only response data are measurable while the actual excitations are unknown, so modal parameter must be extracted only from responses. This paper gives a theoretical formulation for the cross-correlation functions and cross-power spectra between the outputs under the assumption of white-noise excitation. It widens the field of modal analysis under ambient excitation because many classical methods by impulse response functions or frequency response functions can be used easily for modal analysis under unknown excitation. The Polyreference Complex Exponential method and Eigensystem Realization Algorithm using cross-correlation functions in time domain and Orthogonal Polynomial method using cross-power spectra in frequency domain are applied to a steel frame to extract modal parameters under operational conditions. The modal properties of the steel frame from these three methods are compared with those from frequency response functions analysis. The results show that the modal analysis method using cross-correlation functions or cross-power spectra presented in this paper can extract modal parameters efficiently under unknown excitation.

Quantitative analysis of urban intelligence and ranking the potential of individual initiatives within a designed smart growth plan

Smart growth has been gaining increasing attention among academia and practitioners as a new technology-based solution to meet the city disease challenges.In the research,we mainly accomplish two tasks.One builds an evaluation system to measure the smart growth of a city.And the other develops a growth plan.Firstly,coordination coefficient(C value) model is applied to measure the smart degree.To begin with,we divide the indicators into four aspects which involve five parameters.Then,entropy method is used to calculate the weight of every parameter.After normalizing data of indicators,we set up a smart growth indicator evaluation system.Aiming to assessing the detailed performances,we rank the eight cities according to the score of C value which corresponds to our normal cognition.Secondly,based on Salvo combat model and dynamic trend analysis model,We draw up a 20-year growth plan with a period of 5 years for the two cities we choose.The Salvo model is adopted to describe the dynamic process.Dynamic trend analysis model is introduced to gain the optimum solution and the optimal point in every stage.In addition,compared with the point of every stage,we can obtain the proportion of investment in different stages.Thirdly,to evaluate the sensitivity of our model with the OFAT Method,we adjust the parameters k_1,k_2 and O_(ij) approximately.It comes out that the change of k_1,k_2 and O_(ij) has an impact on the C value.But the sensitivity of k_1,k_2 is higher.Lastly,we analyze the influence caused by population growth.To a certain extent,it can be concluded that the plan we made can alleviate the negative impact of population growth through the analysis of the chart.

Facing Both Challenges and Opportunities:How Can Financial Service Firms Survive Under the Pandemic?SOAR Analysis of Three Leading Firms in the Financial Service Industry

After the breakout of COVID-19,many entity industries have to shut down.The rapid decline of money transaction caused by the shutdown of the entity industries has shocked the financial service industry while the increase in digital transactions also offers them opportunities.Facing both challenges and opportunities,financial services firms should change their target and compensation policy during the pandemic to survive.After analysing three major firms in this industry by using SOAR method,we conclude four keys for financial services firms to survive in COVID-19.

基于Clustr-analysis法对过敏性疾病影响因素的计量分析

针对过敏性疾病的影响因素,运用多元线性拟合、Clustr-analysis算法及典型相关分析等方法,构建了基于多元聚集度相关指标的回归函数模型和聚类分析模型.使用MATLAB,SPSS等软件编程,分析过敏性疾病与年龄、季节、性别的相关分布关系.结果表明,60岁附近的人容易感染过敏性疾病,秋季与冬季对过敏性疾病的影响程度大于春季与夏季,绝大多数过敏性疾病种类中男女的患病人数近似相同.基于Clustr-analysis法对过敏性疾病病原体产生情况进行分析,根据7类过敏原种类将26种过敏性疾病分为5类,呼吸类与皮肤类这2种过敏性疾病的类型与其它种类的过敏性疾病类型差别较大.针对过敏性疾病分布特征及其过敏原分类给出相关防范意见.

家庭养老能力评价指标体系构建与实证分析

家庭养老能力事关社会养老服务需求与发展,亟需构建科学有效的家庭养老能力评价指标体系。文章利用CHARLS2018年调查数据,构建出由自我养老能力、配偶养老能力和子女养老能力组成的3个准则指标,共有9个子准则指标和17个观测指标构成的家庭养老能力综合评价指标体系。采用熵权法和复相关系数法确定指标权重,并运用U检验、H检验和空间相关性分析家庭养老能力及其分维度的分布特征。结果显示:子女养老能力、自我养老能力和配偶养老能力权重系数分别为0.555、0.288和0.157。家庭养老能力的得分为0.433±0.091,子女养老能力、自我养老能力和配偶养老能力分维度得分分别为0.121±0.056、0.066±0.019和0.245±0.069,均呈现右偏分布,子女养老能力维度失分最多,自我养老能力维度差异性最大。女性、农村和西部地区老人的家庭养老能力显著弱于男性、城市和东部地区老人。低龄老人自我养老能力和配偶养老能力显著较高,但子女养老能力也显著低于高龄老人。中国家庭养老能力居前三位的是上海市、北京市和新疆维吾尔自治区,云南省、甘肃省和安徽省居后三位。研究发现中国家庭养老能力总体得分不高,自我养老能力与子女养老能力之间呈现“互补”态势。家庭养老能力分布呈现性别、城乡和区域差异性。养老服务体系需基于当前家庭养老能力及其分维度的地区差异性,因地制宜发展。

DIP付费下抑郁症患者住院费用的结构变动及灰色关联分析——以江苏省扬州市某综合性医院为例

[目的]分析综合性医院心理科按病种分值付费(DIP)改革前后抑郁症患者住院费用的变化情况,为完善医保支付方式改革提供实证数据支持。[方法]将样本医院DIP实际执行时间收集抑郁症住院患者分为改革前和改革后两组,采用卡方检验对基本信息进行组间差异性分析;采用结构变动分析和灰色关联分析抑郁症患者次均住院总费用和分项费用变化情况。[结果]DIP改革前后,患者年龄、性别差异无统计学意义(P>0.05);改革后住院天数缩短(P<0.05),次均住院总费用下降(P<0.01);结构变动分析显示2021-2023年抑郁症患者次均住院费用结构变动度(DSV)为33.08%,变动较大;单项次均住院费用结构变动贡献率(CSV)排名前3的是治疗费、医技诊断项目费和药品费,是导致抑郁症患者住院费用变动的主要影响因素。灰色关联分析显示患者次均住院费用中治疗费与总费用的关联系数度为0.930,关联度最高。[结论]DIP改革对优化住院费用结构、缩短平均住院日、降低总费用、提高医务人员合理控费有促进意义,但仍有进一步提升的空间。

石家庄暴雨时空分布特征及灾情评估

基于石家庄市2015—2021年暴雨洪涝灾情资料数据,以及17个国家站及268个区域自动气象站数据,采用气候统计诊断方法分析了石家庄暴雨时空分布的气候特征,并利用灰色关联分析及逐步回归方法,建立了石家庄市暴雨灾情评估及预评估模型.结果表明:①石家庄暴雨频次及强度随时间呈递增趋势,暴雨强度年际变化增大且极端性增强.②石家庄西北部暴雨频次多、强度大,西南部暴雨频次相对较少,但强度最大,其中平山、井陉为大暴雨、特大暴雨高发区,复杂的地理环境使该地区发生暴雨洪涝灾害的风险增加.③由灰色关联分析方法确定的暴雨灾情等级正确率83.33%,能够反映实际暴雨灾情等级,且有利于客观区分同一等级内暴雨灾情大小.④基于气象因子,利用逐步回归方法建立的暴雨灾情评估及预评估模型正确率可达68.75%.

基于改进阿林斯法的数控机床子系统可靠性分配

根据采集到的某国产数控机床的故障信息进行分析整理并进行子系统划分,结合数控机床相关性模型改进可靠性分配方法进行目标值分配.应用层次分析法建立影响因素隶属度集,采取DEMATEL决策实验室分析法确定故障相关数据的中心度影响因素,结合维修性、维修时间、故障停时、故障次数及复杂度确定隶属度函数集,对于各影响因素的权重的确定采用熵权法,进而计算出数控机床的可靠性分配因子.将影响度因素引入阿林斯分配法进行改进,使改进后的方法适用于各子系统串联且存在故障相关性的系统.数值算例表明,相较于传统阿林斯法,本文方法能够减少子系统对故障时间的要求.同时,为验证本文分配结果的合理性,采用蒙特卡洛仿真法以分配结果为基础对目标机床整机进行可靠性预计,计算结果证明了方法的可行性.

基于灰色关联分析的断层突水阶段化感知方法

为提升煤矿断层水害感知水平,提出一种以断层活化演变机制和关键控制因素识别的断层突水阶段化感知方法,通过断层突水演化过程相似模拟试验研究工作面底板与断层破坏的演化特征,以底板破坏带应力、断层裂隙带应力、导水通道内水压等为阶段监测参数,揭示各监测参数与涌水量变化的阶段特征;结合灰色关联性分析法,判定断层突水阶段转化的关键控制因素,进而根据断层突水分析与研究过程,提出断层突水阶段化感知方法。结果表明:底板破坏带、断层裂隙带的应力,导水通道内的水压等监测参数的数值变化特征在断层活化突水过程中呈现出明显的阶段特征,控制因素与涌水量的灰色关联度排序为:底板破坏带应力>断层裂隙带应力>导水通道水压,通过对关键控制因素的识别,可实现断层突水阶段的感知,揭示基于灰色关联分析的感知方法在原理上具备可行性。

骆马湖流域表层沉积物重金属分布特征及风险评价

对骆马湖流域表层沉积物中的重金属分布特征及潜在生态风险进行评估,分析了枯水期、平水期和丰水期3个时段内10种重金属元素(铬、镍、铜、镉、铅、锑、砷、汞、铍、铊)的浓度水平、空间分布和来源。采用潜在生态风险指数法对沉积物中的重金属风险进行了评估。结果显示,镍、铜、镉、铅在部分水期平均浓度高于江苏土壤环境背景值,汞和铊无点位超过背景值,且与其他水体相比,骆马湖流域沉积物重金属污染整体处在中低水平。沉积物中重金属除镉外整体单项生态风险较低,各点位综合潜在风险水平属于中等及以下范畴。相关性分析和主成分分析揭示了重金属污染主要源自工业和农业。

从线性校验子分析方法浅析曾肯成先生的密码分析思想

曾肯成先生于1986年洞察到了密码体制中的熵漏现象,后来在此基础上提出著名的线性校验子分析方法.本文全面剖析了线性校验子分析方法的发展历程,由此深刻揭示了曾先生的密码分析思想的精髓.首先,介绍曾先生通过观察Geffe序列生成器的熵漏现象,提出线性校验子分析方法的朴素思想的过程及其蕴含的思想方法;其次,介绍曾先生通过在Geffe序列生成器基础上凝练出的一般问题,提出解决这一问题的一般方法—线性校验子分析方法的过程及其蕴含的思想方法;再次,介绍曾先生通过分析线性校验子分析方法存在的缺陷,进一步完善和改进线性校验子分析方法的过程及其蕴含的思想方法;最后,通过分析从相关分析方法到线性校验子分析方法的进阶之路,阐述了线性校验子分析方法这把利剑的威力.

基于灰色关联-熵权法的座体注塑工艺参数优化

手持风扇底座具有复杂曲面与多筋结构等复杂的结构特征,这阻碍了材料的流动,可能会使产品产生熔接线、翘曲、体积收缩等缺陷,进而影响产品的表面质量和尺寸精度。为解决上述问题,通过理论算法与有限元仿真相结合开展风扇底座注塑工艺参数的优化研究。首先,根据产品特征确定了型腔数量及浇口位置,初步分析发现产品的缩痕指数相对较大;其次,以翘曲变形和缩痕指数为优化目标,建立中心复合试验方案并开展仿真分析,结合灰色关联与熵权法进行多目标优化,确定了工艺参数对灰色关联度影响的大小程度,依次为熔体温度、模具温度、注射时间、保压压力及保压时间;最后,确定最佳工艺参数组合为熔体温度225℃、模具温度30℃、注射时间5 s、保压压力20 MPa及保压时间30 s。相比初始方案,最佳工艺参数组合下的缩痕指数降低了30.79%,由于加强筋的存在翘曲变形优化前后相差较小。

15个淀粉甘薯主要农艺性状的综合评价

以15个淀粉甘薯品种为试材,采用灰色关联法、DTOPSIS法对淀粉甘薯在郑州栽培的8个农艺性状进行综合评价及分析,结果表明,15个淀粉甘薯品种的8个农艺性状均存在差异显著,变异系数在13.36%~92.01%,产量排名前三的品种为哈密、商薯19和徐薯37;相关分析表明,产量与商品率呈极显著正相关,单株分枝数与商品率呈显著正相关,7个农艺性状对淀粉甘薯产量影响大小依次为商品率>茎直径>单株分枝数>干物质>叶面积>最长蔓长>单株结薯数。DTOPSIS分析结果表明,综合排序前3名与产量前3名排序一致,仅有4个甘薯品种排序有所变化,其余均与鲜薯产量排序一致。综上分析,DOTPSIS法可作为淀粉甘薯品种综合评价的一种方法,筛选出哈密、商薯19和徐薯37可以作为新品种在郑州进行示范推广。

基于Autoformer的铝电解电压偏差预测方法研究

电耗是吨铝成本中一项非常重要的生产指标,而电压偏差则是铝电解生产过程中电耗管理的关键点,因此本文基于中国铝业某铝厂2015—2020年的铝电解数据,对电压偏差的影响特征和预测展开研究。首先,利用分布式梯度增强库(eXtreme Gradient Boosting,XGBoost)算法深度挖掘电压偏差的关联性,并根据相关性得分选取与电压偏差相关性较大的特征。在此基础上,本文构建了基于Autoformer模型的电压偏差预测方法,对2020年前半年的电压偏差数据进行预测,取得了较好的预测效果。将电压偏差的预测结果应用于实际的电解铝生产指导中,可以实现电压偏差的预警,及时调整生产决策,从而减少能耗、稳定电解槽况、延长槽寿命。

基于统计学模型的矿区粉尘污染特征及影响因素的定量分析

针对露天矿粉尘无秩序排放引发的生态环境退化问题,选取河曲露天煤矿粉尘产生区域为研究靶区,利用粉尘监测体系获取靶区TSP、PM10、PM2.5及环境指标数据,结合粉尘浓度对不同粒径粉尘分布差异性进行对比分析,引入空气质量浓度分指数法、Pearson关联矩阵分析法和灰色关联法对靶区内核心污染物、不同粒径粉尘内在关联性及环境指标与粉尘浓度的关联度进行深入探讨,基于单变量、多元线性和主成分得分-多元线性回归分析法对粒子变迁演化规律及环境指标对微粉尘权重的影响规律进行定量解析,同时运用均值误差法对MLR和PCA-MLR模型预测的精确度进行验证。结果表明:(1)区域1(采掘场)和3(煤场)不同粒径粉尘浓度均存在超过现行标准二级限值的情况,区域2(交通干道)仅存在超过一级限值的情况。(2)不同区域粉尘污染能力的强弱与IAQI评估结果一致,均为区域1>3>2;当不同区域TSP浓度一致时,域内粉尘污染能力的强弱顺序转变为区域2>3>1,且各区域核心污染物均为PM2.5。(3)不同区域粉尘浓度线性关系较为显著。(4)不同区域MLR模型演算出的多元线性方程的拟合度排序规律与粉尘浓度Pearson关联度趋于一致,且多变量拟合度优于单变量拟合度,结合MRE法检验出不同区域MLR模型预测精度区域3(3.02%)>2(9.46%)>1(10.75%)。(5)区域1中TSP和PM10与气压呈强正相关,PM2.5与相对湿度呈强负相关;区域2中各粒径粉尘均与温度和风速呈强负相关;区域3中仅与温度呈强负相关。(6)微粉尘权重与环境指标的PCA-MLR模型相对于直接MLR模型,预测精确度提高了56.63%和13.41%。