The Correlation Coefficient of Hesitancy Fuzzy Graphs in Decision Making

The hesitancy fuzzy graphs(HFGs),an extension of fuzzy graphs,are useful tools for dealing with ambiguity and uncertainty in issues involving decision-making(DM).This research implements a correlation coefficient measure(CCM)to assess the strength of the association between HFGs in this article since CCMs have a high capacity to process and interpret data.The CCM that is proposed between the HFGs has better qualities than the existing ones.It lowers restrictions on the hesitant fuzzy elements’length and may be used to establish whether the HFGs are connected negatively or favorably.Additionally,a CCMbased attribute DM approach is built into a hesitant fuzzy environment.This article suggests the use of weighted correlation coefficient measures(WCCMs)using the CCM concept to quantify the correlation between two HFGs.The decisionmaking problems of hesitancy fuzzy preference relations(HFPRs)are considered.This research proposes a new technique for assessing the relative weights of experts based on the uncertainty of HFPRs and the correlation coefficient degree of each HFPR.This paper determines the ranking order of all alternatives and the best one by using the CCMs between each option and the ideal choice.In the meantime,the appropriate example is given to demonstrate the viability of the new strategies.

Reliability of preoperative measurement with standardized templating in Total Knee Arthroplasty

AIM: To investigate the correlation between preoperative measurement in total knee arthroplasty and the prosthetic size implanted. METHODS: A prospective double-blind study of 50 arthroplasties was performed. Firstly, the reliability and correspondence between the size of said measurement and the actual implant utilized was determined. Secondly, the existing correlation between the intra- and interobserver determinations with the intraclass correlation coefficient was analyzed. RESULTS: An overall correspondence of 54%, improving up to 92% when the measured size admitted a difference of one size, was found. Good intra- and interobserver reliability with an intraclass correlation coefficient greater than 0.90(P < 0.001) was also discovered. CONCLUSION: Agreement between the preoperative measurement with standardized acetate templates and the prosthetic size implanted can be considered satisfactory. We thus conclude it is a reproducible technique.

Fuzzy-Weighted Similarity Measures for Memory-Based Collaborative Recommender Systems

Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user weights highly differs from user to user according to his mood and taste. This is usually reflected in the user’s rating scale. Accordingly, many efforts have been done to introduce weights to the similarity measures of CRSs. This paper proposes fuzzy weightings for the most common similarity measures for memory-based CRSs. Fuzzy weighting can be considered as a learning mechanism for capturing the preferences of users for ratings. Comparing with genetic algorithm learning, fuzzy weighting is fast, effective and does not require any more space. Moreover, fuzzy weightings based on the rating deviations from the user’s mean of ratings take into account the different rating scales of different users. The experimental results show that fuzzy weightings obviously improve the CRSs performance to a good extent.

Centrality Measures Based on Matrix Functions

Network is considered naturally as a wide range of different contexts, such as biological systems, social relationships as well as various technological scenarios. Investigation of the dynamic phenomena taking place in the network, determination of the structure of the network and community and description of the interactions between various elements of the network are the key issues in network analysis. One of the huge network structure challenges is the identification of the node(s) with an outstanding structural position within the network. The popular method for doing this is to calculate a measure of centrality. We examine node centrality measures such as degree, closeness, eigenvector, Katz and subgraph centrality for undirected networks. We show how the Katz centrality can be turned into degree and eigenvector centrality by considering limiting cases. Some existing centrality measures are linked to matrix functions. We extend this idea and examine the centrality measures based on general matrix functions and in particular, the logarithmic, cosine, sine, and hyperbolic functions. We also explore the concept of generalised Katz centrality. Various experiments are conducted for different networks generated by using random graph models. The results show that the logarithmic function in particular has potential as a centrality measure. Similar results were obtained for real-world networks.

Selection of extractive agent for mixture chlorobenzene and measurement of VLE data for m-dichlorobenzene-p-dichlorobenzene -o-dichlorobenzene -diphenylamine

Extractive agents of extractive distillation separation for mixtures of dichlorobenzene were analyzed and compared, gas-liquid equilibrium data （VLE data） was measured for dichlorobenzene and diphenylamine, the appropriate extractive agent was selected by relatively volatility, the temperature was studied on the effect of extractive separation. VLE data was measured for dichlorobenzene, the parameters were simulated in Wilson equation. The infinite dilute activity coefficient of dichlorobenzene in diphenylamine were measured by chromatogram apparatus, the model parameters were correlated by the single parameter method for dichlorobenzene and diphenyl -amine, VLE data of m-dichlorobenzene-p- dichlorobenzene -o-dichlorobenzene-diphenylamine system was measured and calculated by six part model parameters. The results of correlation and experiment were provided a basis for study of extractive distillation simulation and experiment in this work.

Test of Normality of Waist Measurement Data of Young Male and Female Adults based on the Quantile - Quantile Plot

This paper investigates the normality of some real data set obtained from waist measurements of a group of 49 young adults. The quantile - quantile （Q-Q） plot and the analysis of correlation coefficients for the Q-Q plot is used to determine the normality or otherwise of the data set. In this regards, the probabilities of the quantiles were computed, modified and plotted. Thereafter the correlation coefficients for the quantile - quantile plots were obtained. Results indicate that at 0.1 level of significance, the data for young adult males of the sample were not normally distributed, and had a mean value that is within the range of low risk, healthwise, whereas the distribution of the data for young female adults showed reasonable normality, but also with a mean value that is within the range of low risk in terms of health condition.

Emulation of Realistic Multi-Path Propagation Channels inside an Anechoic Chamber for Antenna Diversity Measurements

As antennas are inherently included recommended in Over-The-Air (OTA) testing, it is important to also consider realistic channel models for the multiple-input multiple-output (MIMO) device performance evaluation. This paper aims to emulate realistic multi-Path propagation channels in terms of angles of arrivals (AoA) and cross-polarization ratio (XPR) with Rayleigh fading, inside an anechoic chamber, for antenna diversity measurements. In this purpose, a practical multi-probe anechoic chamber measurement system (MPAC) with 24 probe antennas (SATIMO SG24) has been used. However, the actual configuration of this system is not able to reproduce realistic channels. Therefore, a new method based on the control of the SG24 probes has been developed. At first time, this method has been validated numerically through the comparison of simulated and analytical AoA probability density distributions. At the second time, the performance of an antenna diversity system inside the SG24 has been performed in terms of the correlation coefficient and diversity gain (DG) using an antenna reference system. Simulated and measurements results have shown a good agreement.

TESTING SERIAL CORRELATION IN SEMIPARAMETRIC VARYING COEFFICIENT PARTIALLY LINEAR ERRORS-IN-VARIABLES MODEL

The authors propose a V_(N,p) test statistic for testing finite-order serial correlation in asemiparametric varying coefficient partially linear errors-in-variables model.The test statistic is shownto have asymptotic normal distribution under the null hypothesis of no serial correlation.Some MonteCarlo experiments are conducted to examine the finite sample performance of the proposed V_(N,p) teststatistic.Simulation results confirm that the proposed test performs satisfactorily in estimated sizeand power.

基于相关系数-熵-二维云模型的装配式建筑施工风险测度

装配式建筑施工过程要在多维空间中进行,叠加风险高,事故发生率高于传统现浇建筑施工,因此科学、准确地测度装配式建筑施工风险具有重要的现实意义。根据装配式建筑施工的特点,从人员、机械、环境、技术、管理5个维度建立了装配式建筑施工风险测度指标体系,并构建了相关系数-熵-二维云风险测度模型。实例应用结果表明:该测度模型较全面、客观、准确地反映了装配式建筑施工风险要素,能够有效实现装配式建筑施工过程风险的定量化测度,可为装配式建筑施工安全管理提供有力参考和依据。

基于广义条件强度参数的水平和竖向地震动联合选取研究

为了合理地考虑竖向地震作用和实现水平和竖向地震动的联合选取,提出了基于广义条件强度参数的水平和竖向地震动联合选取方法:扩展广义条件强度参数的基本理论,提出水平和竖向地震动广义条件强度参数分布的构建方法,并与“无条件分布”对比,提出基于广义条件强度参数的水平和竖向地震动联合选取方法的基本理论,给出以水平强度参数作为条件的实际算例,利用现有水平-水平、水平-竖向强度参数相关系数模型构建水平和竖向地震动广义条件强度参数目标分布,对目标地震动数据库进行联合选取,将选取结果与传统选取方法进行对比,说明该方法的合理性。结果表明:构建出的水平和竖向广义条件强度参数分布与“无条件”分布之间存在一定差异;水平和竖向地震动联合选取结果与目标理论分布匹配良好;与仅考虑水平向广义条件强度参数地震动选取方法相比,联合选取方法能够考虑竖向地震动特性,并且不会对水平向造成影响,提出的水平和竖向地震动联合选取方法能够更加合理地、全面地考虑水平和竖向地震动特性,为工程结构在水平和竖向地震动作用下的抗震性能研究提供地震动输入基础。

基于相关系数的生物散斑活性表征研究

为了解决传统生物散斑测量结果易受实验参数影响的问题,采用模拟动态光散射及荧光相关光谱技术,用相关系数表征生物散斑活性,搭建了实验装置,并对中药糖浆、酸奶、老酸奶、西红柿、苹果等产品进行了实验测试。结果表明,基于相关系数构造的特征时间指标主要由样品中颗粒运动的速率决定,物理意义明确,几乎不受相机曝光时间、散斑区域等实验参数的影响,平均测量偏差小于5%,易在实际应用中使用。由于农业及医药领域中生物样品的多种特性均与颗粒运动速度有关,该方法可为食品、药品行业提供一种新的无损检测工具。

基于信息量法的湛江地下水资源量估算方法

基于湛江市地下水资源量估算影响因子分析,收集各影响因子数据,进行标准化处理;依据皮尔逊相关系数对各因子筛选,降低估算效率。并利用信息量法衡量各影响因子对地下水资源量估算的贡献率,叠加获取总信息量值确定地下水资源量等级,输出对应等级的地下水资源量估算结果。结果表明,估算结果RMSE值较低,其结果与实际地下水资源量基本一致性,具较高的估算效率。

基于广域量测信息相关性的电力系统同调辨识

提出一种基于广域量测信息相关性识别电力系统同调机群的新方法。针对同调发电机运动轨迹具有一致性或相似性的特征,借鉴基于电力系统模型确定同调机群的方向余弦法,引入广域量测信息相关性来辨识系统的同调机群,在计算系统中各发电机组间的相关系数基础上,提出了划分系统主导同调机群及主导同调机群内部子同调机群的相关同调判据。同时针对广域量测窗口长度对同调辨识结果的影响,进一步提出一种适用于辨识主导同调机群及主导同调机群内部子同调机群的实用鲁棒同调判据。最后将所提方法应用于典型两区域互联交直流系统和南方电网中,分析结果验证了该方法的有效性和可行性。

基于相关系数的证据冲突度量方法

为了更加准确地描述证据间的冲突,在分析证据相关性与证据冲突关系的基础上,给出了证据相关系数的判定准则,基于证据相关系数提出了一种新的证据冲突度量方法,理论证明和数值计算表明该方法可有效表示证据之间的冲突程度,相关系数越大,表明证据间冲突越小,反之亦然。最后通过算例将该冲突度量与其他方法进行对比,结果表明该方法更具全面性和精确性。

基于实测响应空间的负荷动特性分类原理与方法

负荷特性的分类与综合是解决负荷建模中时变性难题的有效途径。于是基于随机过程相关性原理,提出了一种基于实测响应空间的负荷动特性分类方法。该方法以负荷动特性的实测响应空间为特征向量空间,对各个样本的实测响应进行时间坐标的标准化,以计算实测响应空间各样本间的相关系数,并采用系统聚类法按相关系数值进行特性分类。实测响应空间具有能够直接、准确地反映负荷构成的本质特征的优点,一工程应用实例证明了该方法正确有效,实现简便。

大跨屋盖悬挑结构的风荷载分析

针对悬挑结构的上下表面同时受到风荷载作用的特点,提出风洞试验中同步测量的实验方法,分析上下表面风压相关性及其物理意义,给出悬挑结构平均风压和脉动风压的计算方法,探讨了同步测量和异步测量情况下峰值因子的合理取值。

基于向量皮尔森相关系数的组合赋权法

针对多属性决策中属性权重的确定问题,提出了一种基于皮尔森相关系数的主、客观权重的集成方法。用权向量的相关度作为不同赋权方法重要性的度量,意义明确,计算简单,可操作性强。最后采用算例验证了此方法的有效性和实用性。

便携式高频地波雷达东海表面流探测试验

便携式高频地波雷达系统(OSMAR-S)采用了线性中断调频连续波体制和单极子/交叉环紧凑型天线阵,通过双站合成得到海洋表面矢量流.2007年11月在洋山海域进行了OSMAR-S与其他海洋测量设备的表面流现场探测对比验证试验.试验采用了构成二个断面的五个定点和运用漂流浮标的一个动点同时进行的对比监测方式.试验结果表明了OSMAR-S系统的表面流测量效果与其他海洋测量设备的一致性.

不一致邻域粗糙集的不确定性度量和属性约简

不确定性度量和属性约简是邻域粗糙集模型中重要的研究内容.针对目前已有的粗糙集不确定性度量方法难以应用于邻域粗糙集中,同时考虑到现有属性约简算法中很少考虑条件属性之间的关系也会影响约简结果和分类精度.首先分析了不一致邻域粗糙集的相关性质,然后提出了邻域条件熵的不确定性度量方法用来评价约简属性的质量,分析证明了相关的性质定理,接着引入统计学中秩相关系数的概念,通过计算条件属性之间的相关系数来剔除冗余属性,构造了基于相关系数的不一致邻域粗糙集属性约简算法(RNRS).最后在UCI数据集上与现有算法进行了比较分析,实验结果表明,本文的算法可以获取较少的属性特征和较高的分类精度.

基于Fisher最优分割法的机床热关键点优化研究

利用温度测点建立热误差模型时,测点的选取直接影响到模型的精度。采用一种最优化分段方法——Fisher最优分割法,以试验采集到的原始数据作为分析数据,通过计算分类的直径、比较各类中的误差函数,对机床测点变量进行分类,经过对各类中温度变量与热误差之间相关系数的计算,获得用于热误差建模的热关键点,从而完成测点优化。利用多元线性回归方法对其优化出的测点建立热误差模型,与采用变量分组优化选出的温度测点建立的热误差模型进行比较,结果说明Fisher最优分割法可行、实用性强。