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Journal of Advanced Ceramics 2017年第2期6卷 149-156页

作者： Bin DENG Danyu JIANG Department of the Prosthodontics Chinese PLA General Hospital Beijing 100853 China Analysis and Testing Center for Inorganic Materials State Key Laboratory of High Performance Ceramics and Superfine Microstructure Shanghai Institute of Ceramics Shanghai 200050 China

Accurate estimation of Weibull parameters is an important issue for the characterization of the strength variability of brittle ceramics with Weibull statistics. In this paper, a simple method was established for the determination of the Weibull parameters, Weibull modulus m and scale parameter σ0, based on Monte Carlo simulation. It was shown that an unbiased estimation for Weibull modulus can be yielded directly from the Coefficient of variation of the considered strength sample. Furthermore, using the yielded Weibull estimator and the mean value of the strength in the considered sample, the scale parameter σ0 can also be estimated accurately.

关键词： Weibull distribution Weibull parameters strength variability unbiased estimation Coefficient of variation

TOPSIS threat assessment based on the Coefficient of variation

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TOPSIS threat assessment based on the coefficient of variati...

The Coefficient of variation representing the non-uniformity of the strain field and its implication to detect earthquake precursor

第三十九届中国控制会议

作者： Tiandong Sun Jun Wang Chaochen Wang School of Automation Nanjing University of Science and Technology

In the face of multi-target attacks, it is very important to evaluate the threat degree of unknown targets reasonably and accurately and provide data support for subsequent command decision-making. In the traditional calculation of threat degree, the weight coefficient is obtained by expert scoring. This method has strong subjectivity and is far from suitable for urban antiterrorism operations. Therefore, this paper proposes a TOPSIS threat degree ranking method based on the Coefficient of variation, which combines the variation coefficient method with the TOPSIS method, and uses the non-dimensional variable variation coefficient to obtain the weight coefficient, reducing the influence of human factors, and obtains the threat through matrix operation. The results show that the method is objective, accurate and practical.

关键词： Threat assessment Cooperative operations Regional air defense Coefficient of variation

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Earthquake Science 2020年第5期33卷 246-255页

作者： Yonghong Zhao Yue Zhao Xiaofan Li Zhongcheng Cao Zhen Li Muhammad Irfan Ehsan Department of Geophysics Peking UniversityBeijing 100871China

Before the major earthquake or rock damage occurs,it is often accompanied by a sudden change in the degree of non-uniformity of the strain field.In order to find a stronger non-uniformity signal before the rock failure,the Coefficient of variation(Cv)is examined and reformed in this study.We test the Cv calculation way of the"normal-abnormal"model proposed in the previous studies.Based on the analysis of the physical process of rock failure and its relationship to the shear strain field,we construct a new way to calculate the Cv value.The variation of shear strain field on rock sample with the increase of stress is obtained by the digital speckle correlation method(DSCM).The new Cv value calculation way is used to study the non-uniformity of the spatial distribution for the shear strain field.The results show that this Cv calculation way can get more obvious abnormal signals.When the number of observation points are limited,the specific distribution of points can increase the signal strength,which may provide reference for the research on precursor detection of earthquakes.

关键词： rock failure shear strain field non-uniformity Coefficient of variation

Control charts for the Coefficient of variation

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Control charts for the coefficient of variation

Intelligent prediction of slope stability based on visual exploratory data analysis of 77 in situ cases

第十届海峡两岸统计与概率研讨会

作者： Baocai Guo Bing Xing Wang School of Statistics Zhejiang Gongshang University

The Coefficient of variation(CV) has received an extensive attention in quality control. The existing control charts for monitoring the two-sided changes in the CV do not consider the average run length(ARL) unbiased. In practice, practitioner prefers the ARL-unbiased control chart. This paper proposes an ARL-unbiased control chart to monitor the two-sided shifts in the CV. Then an ARL-unbiased synthetic chart in which the CRL sub-chart only needs a lower control limit is proposed to improve the performance of the ARL-unbiased chart. Comparison results show that the synthetic chart outperforms the ARL-unbiased control chart in terms of the ARL. The effects of parameter estimation on the proposed charts are also studied. Finally, a real example is used to illustrate the proposed control charts.

关键词： Coefficient of variation average run length unbiased control chart parameter estimation

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International Journal of Mining Science and Technology 2023年第1期33卷 47-59页

作者： Guangjin Wang Bing Zhao Bisheng Wu Chao Zhang Wenlian Liu Faculty of Land Resources Engineering Kunming University of Science and TechnologyKunming 650093China Yunnan International Technology Transfer Center for Mineral Resources Development and Solid Waste Resource Utilization Kunming 650093China State Key Laboratory of Hydroscience and Engineering Department of Hydraulic EngineeringTsinghua UniversityBeijing 100084China State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan 430071China China Nonferrous Metals Industry Kunming Survey and Design Research Institute Co.Ltd Kunming 650051China

Slope stability prediction research is a complex non-linear system problem.In carrying out slope stability prediction work,it often encounters low accuracy of prediction models and blind data preprocessing.Based on 77 field cases,5 quantitative indicators are selected to improve the accuracy of prediction models for slope stability.These indicators include slope angle,slope height,internal friction angle,cohesion and unit weight of rock and soil.Potential data aggregation in the prediction of slope stability is analyzed and visualized based on Six-dimension reduction methods,namely principal components analysis(PCA),Kernel PCA,factor analysis(FA),independent component analysis(ICA),non-negative matrix factorization(NMF)and t-SNE(stochastic neighbor embedding).Combined with classic machine learning methods,7 prediction models for slope stability are established and their reliabilities are examined by random cross validation.Besides,the significance of each indicator in the prediction of slope stability is discussed using the Coefficient of variation method.The research results show that dimension reduction is unnecessary for the data processing of prediction models established in this paper of slope stability.Random forest(RF),support vector machine(SVM)and k-nearest neighbour(KNN)achieve the best prediction accuracy,which is higher than 90%.The decision tree(DT)has better accuracy which is 86%.The most important factor influencing slope stability is slope height,while unit weight of rock and soil is the least significant.RF and SVM models have the best accuracy and superiority in slope stability prediction.The results provide a new approach toward slope stability prediction in geotechnical engineering.

关键词： Slope stability prediction Machine learning algorithm Dimensionality reduction visualization Random cross validation Coefficient of variation

Reliability assessment of three-dimensional bearing capacity of shallow foundation using fuzzy set theory

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Frontiers of Structural and Civil Engineering 2021年第2期15卷 478-489页

作者： Rajarshi PRAMANIK Dilip Kumar BAIDYA Nirjhar DHANG Department of Civil Engineering Indian Institute of Technology KharagpurKharagpur 721302India

The aim of this study is to investigate the applicability of reliability theory on surface square/rectangular footing against bearing capacity failure using fuzzy set theory in conjunction with the finite element method.Soil is modeled as a three-dimensional spatially varying medium,where its parameters(cohesion,friction angle,unit weight,etc.)are considered as fuzzy variables that maintain some membership functions.Soil is idealized as an elastic-perfectly plastic material obeying the Mohr-Coulomb failure criterion,where both associated and non-associated flow rules are considered in estimating the ultimate bearing capacity of the footing.The spatial variability of the soil is incorporated for both isotropic and anisotropic fields,which are determined by the values of scales of fluctuation in both the horizontal and vertical directions.A new parameter namely,limiting applied pressure at zero failure probability is proposed,and it indirectly predicts the failure probability of the footing.The effect of the Coefficient of variation of the friction angle of the soil on the probability of failure is analyzed,and it is observed that the effect is significant.Furthermore,the effect of the scale of fluctuation on the probability of failure is investigated,and the necessity for considering spatial variability in the reliability analysis is well proven.

关键词： finite element method square footing reliability analysis fuzzy set theory Coefficient of variation spatial variability

Comparative analysis of different static mixers performance by CFD technique:An innovative mixer

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Chinese Journal of Chemical Engineering 2020年第3期28卷 672-684页

作者： M.M.Haddadi S.H.Hosseini D.Rashtchian Martin Olazar Chemical and Petroleum Engineering Department Sharif University of TechnologyTehranIran Department of Chemical Engineering.Ilam University llam 69315-516Iran Department of Chemical Engineering University of the Basque Country(UPV/EHU)Sarriena s/nLeioaSpain

The flow and mixing behavior of two miscible liquids has been studied in an innovative static mixer by using CFD,with Reynolds numbers ranging from 20 to 160.The performance of the new mixer is compared with those of Kenics,SMX,and Komax static mixers.The pressure drop ratio(Z-factor),Coefficient of variation(CoV),and extensional efficiency(α)features have been used to evaluate power consumption,distributive mixing,and dispersive mixing performances,respectively,in all mixers.The model is firstly validated based on experimental data measured for the pressure drop ratio and the Coefficient of variation.CFD results are consistent with measured data and those obtained by available correlations in the literature.The new mixer shows a superior mixing performance compared to the other mixers.

关键词： CFD New static mixer Coefficient of variation Pressure drop ratio

The effect of micro-structural uncertainties of recycled aggregate concrete on its global stochastic properties via finite pixel-element Monte Carlo simulation

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Frontiers of Structural and Civil Engineering 2018年第4期12卷 474-489页

作者： Qingpeng MENG Yuching WU Jianzhuang XIAO Department of Structural Engineering College of Civil EngineeringTongji UniversityShanghai 200092China

In this paper, the effect of micro-structural uncertainties of recycled aggregate concrete (RAC) on its global stochastic elastic properties is investigated via finite pixel-element Monte Carlo simulation. Representative RAC models are randomly generated with various distribution of aggregates. Based on homogenization theory, effects of recycled aggregate replacement rate, aggregate volume fraction, the unevenness of old mortar, proportion of old mortar, aggregate size and elastic modulus of aggregates on overall variability of equivalent elastic properties are investigated. Results are in a good agreement with experimental data in literature and finite pixel-element method saves the computation cost. It is indicated that the effect of mesoscopic randomness on global variability of elastic properties is considerable.

关键词： RAC Monte Carlo analysis stochastic finite pixel-element method homogenization Coefficient of variation recycled-aggregate concrete Stochastic Elastic properties Experimental data Monte Carlo technique AKT1 gene aggregates homogenization Coefficient of variation

Water quality evaluation of Haihe River with fuzzy similarity measure methods

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Journal of Environmental Sciences 2013年第10期25卷 2041-2046页

作者： Xiaojing Wang Zhihong Zou Hui Zou School of Economic and Management Beihang University Department of Applied Mathematics College of ScienceChina Agricultural University

Fuzzy similarity measures, which are used to judge the closeness of two fuzzy sets, are presented to evaluate the water quality of the Haihe River. Based on the membership functions and Coefficient of variation as the weights, four fuzzy similarity measures （including Lattice similarity measure, Hamming similarity measure, Euclidean similarity measure and the max-min similarity measure） are used to classify the 299 samples into the proper water quality standard ranks. The results are compared with the traditional distance discriminant methods. The calculation of two traditional distance discriminant methods （both Euclidean distance and absolute value distance） is also based on the use of coefficients of variation as the weights. Without the Lattice similarity measure, for this method loses some information, the correct assignment of samples classified into the same water quality ranks is 75.92% with the other three similarity measures and two distance discriminant methods. This result shows the reliability of the five methods. Only considering the three similarity measures, there were only 1.01% of the samples that did not classify to the same ranks, while the corresponding ratio of the two distance discriminant methods was 5.69%. The results of leave-one-out cross validation show that more than 88% of the samples are classified to the proper ranks, which demonstrates that the similarity measures are suitable to evaluate the water quality of the Haihe River.

关键词： similarity measure distance discriminant Coefficient of variation membership function

Flood risk assessment using the CV-TOPSIS method for the Belt and Road Initiative:an empirical study of Southeast Asia

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Ecosystem Health and Sustainability 2020年第1期6卷 321-332,320页

作者： Yan An Xianchun Tan Baihe Gu Kaiwei Zhu Institutes of Science and Development Chinese Academy of SciencesBeijingChina

Instruction:The countries along the Belt and Road Initiative remain high exposure and vulnerability to climate extremes.Southeast Asia,a significant part of the Belt and Road Initiative,suffers a lot from flood disasters.This study assessed the flood disaster risk from 1990–2015 in all 11 Southeast Asian countries.A model integrating the Coefficient of variation approach and the Technique for Order Preference by Similarity to Ideal Solution method was introduced to analyze the flood disaster data.Considering that populations living in areas where elevation is below 5 m and land area where elevation is below 5 m have reached 11.86%and 3.54%(2015),respectively,the two indicators were opted for to propose new metrics for flood disaster risk assessment.Outcomes:Our findings show that the flood disaster risk in Southeast Asia appeared very high during most of the study period.Indonesia had an extremely high flood disaster risk,followed by Vietnam,whereas Laos,Malaysia,Brunei,and Timor Leste had lower flood risks.The model introduced in this paper is quite simple and easy to understand,providing accessible flood risk information for decision makers.Conclusion:The results we obtained have practical implications for land use and investment activities in Southeast Asia.

关键词： Flood risk assessment technique for order preference by similarity to ideal solution Coefficient of variation Southeast Asia