Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.

A Note on the Relationship between the Pearson Product-Moment and the Spearman Rank-Based Coefficients of Correlation

This note derives the relationship between the Pearson product-moment coefficient of correlation and the Spearman rank-based coefficient of correlation for the bivariate normal distribution. This new derivation shows the relationship between the two correlation coefficients through an infinite cosine series. A computationally efficient algorithm is also provided to estimate the relationship between the Pearson product-moment coefficient of correlation and the Spearman rank-based coefficient of correlation. The algorithm can be implemented with relative ease using current modern mathematical or statistical software programming languages e.g. R, SAS, Mathematica, Fortran, et al. The algorithm is also available from the author of this article.

The Application of Pearson Correlational Analysis Method in Air Quality Analysis of Beijing-Tianjin-Hebei Region

Based on the analysis of monitoring data on six pollution indexes of SO2, NO2, CO, O3, PM10 and PM2.5 from 53 monitoring points in 7 cities, including Beijing, Tianjin, Shijiazhuang, etc., from April 8 of 2014 to July 23 of 2014, this article adopted Pearson correlation coefficient method to determine the relevance among each pollutant of these cities with the help of SPSS. The results showed that such three leading indexes as SO2, PM10 and PM2.5 had strong correlation in Beijing, Tianjin and main cities of Hebei. Finally, some suggestions and preventive measures for the cooperative governance of air pollution in Beijing-Tianjin-Hebei Region were put forward, hoping this can help them.

基于Pearson相关性分析的双V型永磁同步电机失磁故障动态识别方法

针对电驱动系统用高功率密度永磁驱动电机存在的不可逆退磁问题,以一款8极48槽的双V型永磁同步电机为例对退磁故障的动态识别方法进行了研究。在考虑电机闭合磁路对永磁体退磁故障影响的基础上,通过分析高退磁率电机模型退磁前后的空载和负载参数变化,采用Pearson相关性分析的方法提取了表征退磁故障的特征参量,给出了一种退磁故障的动态识别方法,并分析了转速和电流对特征参量的影响,完成了对退磁故障动态识别方法的修正。通过仿真和实验测试的方法对退磁故障动态识别方法的准确性进行了验证,结果表明,仿真结果的误差为0.68%,实验测试的预测结果最大误差为1.765%,误差均在可接受范围内。

Pearson＇s Correlation Coefficient： A More Realistic Threshold for Applications on Autonomous Robotics

Many applications for control of autonomous platform are being developed and one important aspect is the excess of information, frequently redundant, that imposes a great computational cost in data processing. Taking into account the temporal coherence between consecutive frames, the PCC （Pearson＇s Correlation Coefficient） was proposed and applied as： discarding criteria methodology, dynamic power management solution, environment observer method which selects automatically only the regions-of-interest; and taking place in the obstacle avoidance context, as a method for collision risk estimation for vehicles in dynamic and unknown environments. Even if the PCC is a great tool to help the autonomous or semi-autonomous navigation, distortions in the imaging system, pixel noise, slight variations in the object＇s position relative to the camera, and other factors produce a false PCC threshold. Whereas there are homogeneous regions in the image, in order to obtain a more realistic Pearson＇s correlation, we propose to use some prior known environment information.

Inversion of time-domain airborne EM data with IP effect based on Pearson correlation constraints

Due to the induced polarization(IP)eff ect,the sign reversal often occurs in timedomain airborne electromagnetic(AEM)data.The inversions that do not consider IP eff ect cannot recover the true umderground electrical structures.In view of the fact that there are many parameters of airborne induced polarization data in time domain,and the sensitivity diff erence between parameters is large,which brings challenges to the stability and accuracy of the inversion.In this paper,we propose an inversion mehtod for time-domain AEM data with IP effect based on the Pearson correlation constraints.This method uses the Pearson correlation coeffi cient in statistics to characterize the correlation between the resistivity and the chargeability and constructs the Pearson correlation constraints for inverting the objective function to reduce the non uniqueness of inversion.To verify the eff ectiveness of this method,we perform both Occam’s inversion and Pearson correlation constrained inversion on the synthetic data.The experiments show that the Pearson correlation constrained inverison is more accurate and stable than the Occam’s inversion.Finally,we carried out the inversion to a survey dataset with and without IP eff ect.The results show that the data misfit and the continuity of the inverted section are greatly improved when the IP eff ect is considered.

基于暂态电压Pearson相关系数的柔性直流配电网纵联保护方法

柔性直流配电网故障特征复杂,快速可靠的故障保护方法是柔性直流配电网亟需突破的关键技术。基于此提出了一种基于直流线路限流电抗器暂态电压皮尔逊(Pearson)相关系数的直流配电网纵联保护方法。首先,分析了区内外不同故障类型下直流线路两端限流电抗器暂态电压的特征差异。其次,利用正、负极线路电压的变化率构成保护启动判据,通过直流线路两端限流电抗器暂态电压的Pearson相关系数识别区内、外故障,并利用直流线路正负极电压变化率间的正负关系设计故障选极判据。最后,在Matlab/Simulink仿真软件中搭建柔性直流配电网仿真模型验证所提保护方法的可行性。结果表明所提保护方法能满足柔性直流配电网保护速动性和选择性的要求,且耐过渡电阻能力强,受通信延迟影响小,具有一定的抗干扰能力。

Statistical analysis of fracture properties based on particle swarm optimization and Pearson correlation coefficient method

Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.

基于Pearson相关性的VAR模型煤电水煤比寻优应用

本文为解决350MW燃煤机组在煤质频繁变化情况下水煤比失衡的问题,使用向量自回归(VAR)模型在机组参数波动工况下进行水煤比寻优。通过使用Pearson相关系数分析机组运行参数,确定寻优模型的输入数据,计算VAR模型最优阶数,并建立VAR模型从多个参数的时间序列寻找对应工况下水煤比最优值,同时使用三种不同分析方法确保该最优值的准确性和安全性。实践证明,该方法能有效解决机组由于煤质频繁变化导致锅炉给水策略不适配引发的主蒸汽温度和主蒸汽压力偏差大等问题。

Pearson correlation and transfer entropy in the Chinese stock market with time delay

Correlations between two time series,including the linear Pearson correlation and the nonlinear transfer entropy,have attracted significant attention.In this work,we studied the correlations between multiple stock data with the introduction of a time delay and a rolling window.In most cases,the Pearson correlation and transfer entropy share the same tendency,where a higher correlation provides more information for predicting future trends from one stock to another,but a lower correlation provides less.Considering the computational complexity of the transfer entropy and the simplicity of the Pearson correlation,using the linear correlation with time delays and a rolling window is a robust and simple method to quantify the mutual information between stocks.Predictions made by the long short-term memory method with mutual information outperform those made only with selfinformation when there are high correlations between two stocks.

基于Pearson相关系数与广义S变换的低压直流微电网的故障选线方法

针对低压直流微电网线路的故障选线方法的研究有限,提出一种基于Pearson相关系数与广义S变换的故障选线方法。首先,介绍了低压直流微电网的一般组成。在此基础上,研究了低压直流微电网的单极故障以及极间故障的故障特征,提出选线方法,对各线路正负极首末端电流差进行Pearson相关系数计算来确定故障线路。然后对所选故障线路正负线路首端的电流量进行广义S变换,计算出其能量和的比值判别故障极性或者极间故障。最后,在PSCAD/EMTDC中搭建出低压直流微电网模型以输出各线路电流数据,并利用Matlab对数据进行仿真。结果表明,所提选线方法直接有效,且耐受过渡电阻的能力较强。

基于Pearson-KPCA和LSTM的伺服电机滚动轴承剩余寿命预测

针对伺服电机滚动轴承的寿命预测,提出一种基于皮尔逊相关系数及核主成分分析的长短时记忆网络预测方法。提取滚动轴承的时、频域信号,通过移动平均法进一步获取相关特征,并采用皮尔逊相关系数筛选高度相关特征指标,利用KPCA提取高度相关特征指标中的若干主成分;将第一主成分作为长短时记忆网络模型的输入对滚动轴承进行剩余寿命预测。采用IMS轴承数据集进行验证,得到的轴承寿命预测RMSE值和可决策系数值分别为0.0543和0.989。将其与长短期记忆网络模型和BP神经网络的预测结果进行对比,证明所提方法具有较高的精度。

基于聚类分析和Pearson相关系数法的电网负荷数据清洗与去重

针对电网负荷数据存在冗余和价值密度低等问题,本文提出一种结合K-means算法与Pearson相关系数计算的集成学习方法,对负荷数据进行清洗与去重。设置仿真实验将某地区连续730日的负荷数据进行聚类、切片、排序、比对、去重等分析处理,得到清洗后的新数据集,将新数据集与原数据集代入相同的BP神经网络模型和随机森林模型进行负荷预测,实验结果表明新旧数据集具有相似的特征特性与数据挖掘潜力。与传统的数据去重方法相比,本文提出的数据清洗策略在进行训练集的预处理时,效率和准确度方面均有更好表现,可以为训练用于负荷预测的网络模型提供支持。

Improved Representation of Biological Information by Using Correlation as Distance Function for Heatmap Cluster Analysis

Heatmap cluster figures are often used to represent data sets in the?omic sciences. The default option of the frequently used R heatmap function is to cluster data according to Euclidean distance, which groups data mainly to their numerical value and not to its relative behaviour. The disadvantage of using the default clustering?dendrograms of R is demonstrated. Instead, a script is provided that uses correlation as distance function, which better reveals biologically meaningful information. This optimized script was used to detect heterotic groups in Vitamaize hybrids (purple maize with high nutraceutical value). A field trial with different genetic combinations was performed through an agricultural phenomics approach (holistic evaluation of the phenotype). The grain yield data and other phenotypic variables were represented through heatmap figures. In the data set of Mexican tropical maize germplasm, at least three heterotic groups were detected, in contrast to only two heterotic groups reported earlier in temperate yellow maize from USA and Europe. This optimized script for heatmap correlation bicluster can also be used to better represent metabolomic fingerprints and transcriptomic data sets.

Geostatistical Correlation of Aquifer Potentials in Abia State, South-Eastern Nigeria

In this paper, a collection of statistical correlation methods is used in the study of aquifer potentials in Abia State of south-eastern Nigeria. The Physiology, geomorphology and hydrogeology of the area are first presented. Sixty-six Vertical Electrical Sounding (VES) data sets are used to determine the aquifer. Demographic studies are then carried out in 220 communities in order to determine the relationship between population size on one hand and a unit draw-down of wells due to groundwater abstraction on the other. The relationship between geological Formation, aquifer potentials and depth of boreholes are then calculated using Pearson’s correlation matrix. Results show that the mean population of persons appears to be higher in Bende-Ameki Formation (of Eocene-Oligocene age) and the late Tetiary-Early Quaternary Coastal Plain Sands, than in the Cretaceous shale Formation of Asata Nkporo. The mean population of persons sitting on these Formations is 31,200, 18,370 and 5400 respectively. Furthermore, it is observed that a population increase of about 50 persons in a community in Abia State is accompanied by a unit volume (1 m3) draw-down of wells due to groundwater abstraction. It is therefore concluded that population size is positively correlated with groundwater abstraction, aquifer potentials and geological Formation favouring aquifer in Abia State.

基于Pearson相关性的雷达交叠信号识别

针对复杂电磁环境下多部雷达同时到达信号频域交叠时难以分选识别的问题,分析了信号交叠对于雷达信号识别模块性能的影响;在此基础上面向识别需求,基于Pearson算法研究了交叠信号分选的处理方法。从信息论视角来说,两个信号脉冲波形相关性越弱,则其所表达的信息量越大,特征相关度越低。在信号脉冲数一定时,基于Pearson算法可以选择相关性较弱的信号脉冲载波,以削弱同时信号交叠的影响。通过实验,发现利用选择后的弱相关信号脉冲载波特征来表达信号特性,能有效降低数据维度,尽可能减少信息丢失,有利于达到鲁棒的识别效果,因此该方法可为同时到达信号交叠下的信号识别提供有效途径参考。

The levels of serum cystatin C, brain natriuretic peptide in traumatic patients and correlation analysis with traumatic severity

Objective:To observe the levels of serum cystatin C (Cys C), brain natriuretic peptide (BNP) in traumatic patients and correlation analysis with traumatic severity.Methods:120 emergency traumatic patients in emergency department of our hospital were rolled from December 2015 to December 2016, who were divided into minor trauma group (n=41), severe trauma group (n=43) and critical trauma group (n=36) according to the injury severity score (ISS). The levels of serum Cys C, BNP of the patients in the 3 groups were detected on 0 h, 24 h, 3 d and 7 d after admission respectively. Pearson correlation analysis of the levels of serum Cys C, BNP and ISS.Results: There were no significant differences in the levels of serum Cys C, BNP on 0 hours between the three groups;There were no significant differences in the levels of serum Cys C, BNP on 0 h, 24 h, 3 d and 7 d in minor trauma group;The levels of serum Cys C, BNP on 24 h, 3 d and 7 d were all higher than those of 0 h in severe trauma group, and the levels of serum Cys C on 3 d and 7 d were both higher than those of 24 h;The levels of serum Cys C, BNP on 24 h, 3 d and 7 d were all higher than those of 0 h in critical trauma group, the levels of serum Cys C, BNP on 3 d and 7 d were both higher than those of 24 h, and the levels of serum Cys C on 7 d were higher than those of 3 d;The levels of serum Cys C, BNP in severe trauma and critical trauma groups were significantly higher compared with minor trauma group on 24 h, 3 d and 7 d. Pearson correlation analysis, the level of serum Cys C were positively correlated with ISS, the level of serum BNP were positively correlated with ISS.Conclusion:Different levels of traumatic patients had different levels of serum Cys C, BNP increased at different times. Pearson correlation analysis showed that the levels of serum Cys C, BNP were both positively correlated with traumatic severity, which suggested that the levels of serum Cys C, BNP may be important indicators of traumatic severity and could provide important reference value for clinical evaluation of traumatic severity.

中高应变速率轧制AZ31镁合金板的抗拉强度预测

本文采集了不同轧制温度、应变速率以及压下量等三个工艺参数下中高应变速率轧制的AZ31镁合金抗拉强度的27组样本,通过惯性权重、学习因子的改进和引入变异操作对PSO-BP神经网络进行改进,并与BP、PSO-BP神经网络对比,进行抗拉强度的预测。结果表明:BP神经网络不能预测AZ31镁合金抗拉强度的非线性变化,PSO-BP神经网络和改进的PSO-BP(IPSO-BP)神经网络均能较好地预测AZ31镁合金抗拉强度的非线性变化;这三个模型中IPSO-BP神经网络预测最为准确,相较于PSO-BP神经网络,其平均绝对误差从15.3764降低至3.4288,平均相对误差从5.94%降低至1.32%,均方误差从251.3662降低至20.7199,相关系数从0.7753提高至0.8937;通过Pearson相关性计算判断出应变速率、压下量对抗拉强度的影响均大于轧制温度,而应变速率与抗拉强度呈负相关关系,压下量与抗拉强度呈正相关关系。

社交焦虑、病耻感在精神分裂症患者正念、认知中链式中介路径研究

目的研究社交焦虑、病耻感在精神分裂症(SP)患者正念、认知中链式中介路径。方法选取2022年9月—2023年9月收治的SP 87例,采用一般资料调查问卷、精神疾病病耻感量表、交往焦虑量表、正念注意觉知量表、韦氏成人智力测试对其展开问卷调查,采用Pearson和结构方程模型分析社交焦虑、病耻感、正念、认知间的关系。结果不同性别、年龄、病程、受教育层次、体质量指数、疾病分型SP患者智商值比较差异无统计学意义(P>0.05)。Pearson相关分析显示,SP患者病耻感与社交焦虑呈正相关,正念与社交焦虑、病耻感呈负相关,认知与社交焦虑、病耻感呈负相关,认知与正念呈正相关(P<0.01)。结构方程模型拟合指数χ^(2)/df=4.935,RMSEA=0.051,TLI=0.963,CFI=0.977,NFI=0.952;Bootstrap程序检验显示,正念对认知有直接效应,也可通过社交焦虑、病耻感的平行中介效应或社交焦虑→病耻感链式中介效应间接起正向效应。结论临床在SP患者认知功能康复治疗中,应重视正念干预在不同作用路径之间的效应,并以路径为依据,采取合适方式提高患者认知功能。

老年肺癌化疗患者化疗相关性味觉改变与生存质量的Pearson相关分析

目的:基于Pearson相关分析,探讨老年肺癌化疗患者化疗相关性味觉改变(CITA)与生存质量的关系。方法:采用简单随机抽样法选择2021年1月1日~2022年12月31日收治的老年肺癌化疗患者112例作为研究对象。采用一般资料调查表、化疗相关性味觉改变量表(CiTAS)、肺癌患者生命质量测定量表(QLICP-LU)对患者进行信息收集,另采用SPSS 26.0软件对患者CITA与生存质量进行Pearson相关分析。结果:本研究发放问卷112份,其中2份问卷填写过程中受到外界人为因素干扰,予以剔除,回收有效问卷110份,回收有效率为98.21%。本研究110例患者的CiTAS总分范围4.17~7.60分,中位CiTAS总分为6.13(5.53,6.23)分。不同性别、年龄、TNM分期、口腔清洁方式、化疗方案、吸烟史情况的老年肺癌化疗患者,CiTAS和QLICP-LU总分差异无统计学意义(P>0.05);不同口腔干燥情况、口腔疼痛情况的老年肺癌化疗患者,CiTAS和QLICP-LU总分差异有统计学意义(P<0.01)。老年肺癌化疗患者CiTAS各领域评分及总分与QLICP-LU各领域评分及总分均呈现负相关(r=-0.408~-0.853,P<0.01)。结论:老年肺癌化疗患者CITA与生存质量关系紧密,且目前老年肺癌化疗患者CITA较为严重,根据引起CITA的主要因素制订并实施相应护理措施,有助于改善患者味觉变化,对提高患者生存质量也有积极影响。