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Markov-Switching Time-Varying Copula Modeling of Dependence Structure between Oil and GCC Stock Markets 被引量:1
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作者 Heni Boubaker Nadia Sghaier 《Open Journal of Statistics》 2016年第4期565-589,共25页
This paper proposes a Markov-switching copula model to examine the presence of regime change in the time-varying dependence structure between oil price changes and stock market returns in six GCC countries. The margin... This paper proposes a Markov-switching copula model to examine the presence of regime change in the time-varying dependence structure between oil price changes and stock market returns in six GCC countries. The marginal distributions are assumed to follow a long-memory model while the copula parameters are supposed to evolve according to the Markov-switching process. Furthermore, we estimate the Value-at-Risk (VaR) based on the proposed approach. The empirical results provide evidence of three regime changes, representing precrisis, financial crisis and post-crisis, in the dependence structure between energy and GCC stock markets. In particular, in the pre- and post-crisis regimes, there is no dependence, while in the crisis regime, there is significant tail dependence. For OPEC countries, we find lower tail dependence whereas in non-OPEC countries, we see upper tail dependence. VaR experiments show that the Markov-switching time- varying copula model performs better than the time-varying copula model. 展开更多
关键词 time-varying copulas Markov-Switching model Oil Price Changes GCC Stock Markets VAR
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Mixed D-vine copula-based conditional quantile model for stochastic monthly streamflow simulation 被引量:2
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作者 Wen-zhuo Wang Zeng-chuan Dong +3 位作者 Tian-yan Zhang Li Ren Lian-qing Xue Teng Wu 《Water Science and Engineering》 EI CAS CSCD 2024年第1期13-20,共8页
Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate b... Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months.To address this limitation,this study developed a mixed D-vine copula-based conditional quantile model that can capture temporal correlations.This model can generate streamflow by selecting different historical streamflow variables as the conditions for different months and by exploiting the conditional quantile functions of streamflows in different months with mixed D-vine copulas.The up-to-down sequential method,which couples the maximum weight approach with the Akaike information criteria and the maximum likelihood approach,was used to determine the structures of multivariate Dvine copulas.The developed model was used in a case study to synthesize the monthly streamflow at the Tangnaihai hydrological station,the inflow control station of the Longyangxia Reservoir in the Yellow River Basin.The results showed that the developed model outperformed the commonly used bivariate copula model in terms of the performance in simulating the seasonality and interannual variability of streamflow.This model provides useful information for water-related natural hazard risk assessment and integrated water resources management and utilization. 展开更多
关键词 Stochastic monthly streamflow simulation Mixed D-vine copula Conditional quantile model Up-to-down sequential method Tangnaihai hydrological station
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On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis
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作者 Fangyi Li Dachang Zhu Huimin Shi 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第5期1981-1999,共19页
In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems... In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem. 展开更多
关键词 Mixed uncertainty probability model convex model time-variant reliability analysis
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Time-Varying Mesh Stiffness Calculation and Dynamic Modeling of Spiral Bevel Gear with Spalling Defects
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作者 Keyuan Li Baijie Qiao +2 位作者 Heng Fang Xiuyue Yang Xuefeng Chen 《Journal of Dynamics, Monitoring and Diagnostics》 2024年第2期143-155,共13页
Time-varying mesh stiffness(TVMS)is a vital internal excitation source for the spiral bevel gear(SBG)transmission system.Spalling defect often causes decrease in gear mesh stiffness and changes the dynamic characteris... Time-varying mesh stiffness(TVMS)is a vital internal excitation source for the spiral bevel gear(SBG)transmission system.Spalling defect often causes decrease in gear mesh stiffness and changes the dynamic characteristics of the gear system,which further increases noise and vibration.This paper aims to calculate the TVMS and establish dynamic model of SBG with spalling defect.In this study,a novel analytical model based on slice method is proposed to calculate the TVMS of SBG considering spalling defect.Subsequently,the influence of spalling defect on the TVMS is studied through a numerical simulation,and the proposed analytical model is verified by a finite element model.Besides,an 8-degrees-of-freedom dynamic model is established for SBG transmission system.Incorporating the spalling defect into TVMS,the dynamic responses of spalled SBG are analyzed.The numerical results indicate that spalling defect would cause periodic impact in time domain.Finally,an experiment is designed to verify the proposed dynamic model.The experimental results show that the spalling defect makes the response characterized by periodic impact with the rotating frequency of spalled pinion. 展开更多
关键词 dynamic modeling slice method SPALLING spiral bevel gear time-varying mesh stiffness(TVMS)
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Copula模型的改进及其应用
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作者 夏喆 余浪 黄洁莉 《统计与决策》 CSSCI 北大核心 2024年第10期58-62,共5页
Copula模型能精确计算投资组合尾部风险,弥补Person相关系数的不足。文章基于信用风险Cop⁃ula模型,探讨了不同抽样算法在信贷投资组合中的应用问题,优化重要性抽样和交叉熵算法,测试了高斯及t-Copula模型的风险计算算法,并通过数值模拟... Copula模型能精确计算投资组合尾部风险,弥补Person相关系数的不足。文章基于信用风险Cop⁃ula模型,探讨了不同抽样算法在信贷投资组合中的应用问题,优化重要性抽样和交叉熵算法,测试了高斯及t-Copula模型的风险计算算法,并通过数值模拟予以检验,结果表明:朴素蒙特卡罗模拟的精度和效率较低;重要性抽样算法通过解析逼近显著降低计算方差,提高精度,但求解复杂且耗时;交叉熵算法同样有效,但需自适应算法求解优化问题。算例分析结果表明,基于不同场景选择Copula模型,可提高信贷投资组合风险计算精度和效率。 展开更多
关键词 投资组合 风险分析 copula模型
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基于EVT-Copula-CoVaR的石油市场对中国碳市场风险溢出效应研究
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作者 陈迪 胡海青 张欢 《运筹与管理》 CSSCI CSCD 北大核心 2024年第2期108-115,共8页
石油是全球碳排放的重要来源,而碳排放权交易市场是节能减排的有效工具,将石油市场与碳市场进行关联分析,特别是考虑到中国特殊的制度设计问题,测度国内外石油市场对中国不同碳市场的风险溢出效应受到理论界和实务界的关注与重视。本文... 石油是全球碳排放的重要来源,而碳排放权交易市场是节能减排的有效工具,将石油市场与碳市场进行关联分析,特别是考虑到中国特殊的制度设计问题,测度国内外石油市场对中国不同碳市场的风险溢出效应受到理论界和实务界的关注与重视。本文在考虑到市场极端风险的基础上,选取2014年4月2日至2019年10月31日国内外石油市场与5个交易较活跃的中国碳市场的碳价格数据作为研究样本,构建EVT-Copula-CoVaR模型量化分析石油市场对中国碳市场的风险溢出效应。研究表明,国内外石油市场的风险事件对各碳市场均产生正向溢出效应,且对比不同碳市场可发现同一置信水平下石油市场对碳市场的风险溢出强度从大到小依次为:湖北、广东、深圳、北京、上海。同时,对比国内外石油市场发现,国外石油市场对碳市场的风险溢出效应更大。研究结论有助于丰富和延伸我国碳市场与石油市场之间的联动机制研究,同时对我国碳市场的稳定发展及风险管理具有重要的意义。 展开更多
关键词 石油市场 碳市场 风险溢出效应 EVT-copula-CoVaR
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Time-variant fragility analysis of the bridge system considering time-varying dependence among typical component seismic demands 被引量:7
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作者 Song Shuai Qian Yongjiu +2 位作者 Liu Jing Xie Xiaorui Wu Gang 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2019年第2期363-377,共15页
This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Bas... This paper presents a copula technique to develop time-variant seismic fragility curves for corroded bridges at the system level and considers the realistic time-varying dependence among component seismic demands. Based on material deterioration mechanisms and incremental dynamic analysis, the time-evolving seismic demands of components were obtained in the form of marginal probability distributions. The time-varying dependences among bridge components were then captured with the best fitting copula function, which was selected from the commonly used copula classes by the empirical distribution based analysis method. The system time-variant fragility curves at different damage states were developed and the effects of time-varying dependences among components on the bridge system fragility were investigated. The results indicate the time-varying dependence among components significantly affects the time-variant fragility of the bridge system. The copula technique captures the nonlinear dependence among component seismic demands accurately and easily by separating the marginal distributions and the dependence among them. 展开更多
关键词 system FRAGILITY CHLORIDE corrosion time-varying DEPENDENCE copula function probabilistic seismic demand
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基于扭曲混合Copula函数的均值-ES模型的构建与应用
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作者 陈振龙 刘俊杰 郝晓珍 《统计与信息论坛》 CSSCI 北大核心 2024年第12期3-14,共12页
考虑到金融资产间的极端尾部相依结构对投资组合风险优化的影响,构建基于扭曲混合Copula函数的均值-ES模型,通过扭曲函数来刻画金融资产间的极端尾部特征,获得一定预期收益下的投资组合优化策略。首先,将均值-ES模型中用于刻画相依结构... 考虑到金融资产间的极端尾部相依结构对投资组合风险优化的影响,构建基于扭曲混合Copula函数的均值-ES模型,通过扭曲函数来刻画金融资产间的极端尾部特征,获得一定预期收益下的投资组合优化策略。首先,将均值-ES模型中用于刻画相依结构的协方差矩阵扩展为可以描述极端尾部相依结构的扭曲混合Copula函数,构建了基于扭曲混合Copula函数的均值-ES模型;其次,提出了基于该模型的ES估计算法;最后,通过数值模拟和实证研究说明了该模型用于刻画极端尾部相依结构特征并进行投资组合优化的效果。数值模拟的结果表明,基于扭曲混合Copula函数的均值-ES模型适用于具有极端尾部相依结构特征的数据集;利用该模型进行投资组合优化后收益明显提升,风险显著降低。实证研究的结果表明,该模型能显著提升最优投资组合的样本外策略表现,同时返回检验的结果也验证了使用该模型对投资组合优化进行风险预测的准确性。因此,基于扭曲混合Copula函数的均值-ES模型弥补了传统投资组合风险优化模型中忽略极端尾部风险的不足,推动了扭曲混合Copula函数在投资组合风险优化中的应用研究。 展开更多
关键词 极端尾部相依结构 扭曲混合copula函数 均值-ES模型 风险优化 投资组合
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Neural Network and GBSM Based Time-Varying and Stochastic Channel Modeling for 5G Millimeter Wave Communications 被引量:7
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作者 Xiongwen Zhao Fei Du +4 位作者 Suiyan Geng Ningyao Sun Yu Zhang Zihao Fu Guangjian Wang 《China Communications》 SCIE CSCD 2019年第6期80-90,共11页
In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN mod... In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN models are developed for modeling of path loss together with shadow fading(SF)and joint small scale channel parameters.The NN models can predict path loss plus SF and small scale channel parameters accurately compared with measurement at 26 GHz performed in an outdoor microcell.The time-varying path loss and small scale channel parameters generated by the NN models are proposed to replace the empirical path loss and channel parameter random numbers in GBSM-based framework to playback the measured channel and match with its environment.Moreover,the sparse feature of clusters,delay and angular spread,channel capacity are investigated by a virtual array measurement at 28 GHz in a large waiting hall. 展开更多
关键词 time-varying CHANNEL NEURAL network CLUSTER CHANNEL modeling VIRTUAL array measurement 5G
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Optimal Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model 被引量:9
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作者 熊智华 ZHANG Jie 董进 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2008年第2期235-240,共6页
A batch-to-batch optimal iterative learning control (ILC) strategy for the tracking control of product quality in batch processes is presented. The linear time-varying perturbation (LTVP) model is built for produc... A batch-to-batch optimal iterative learning control (ILC) strategy for the tracking control of product quality in batch processes is presented. The linear time-varying perturbation (LTVP) model is built for product quality around the nominal trajectories. To address problems of model-plant mismatches, model prediction errors in the previous batch run are added to the model predictions for the current batch run. Then tracking error transition models can be built, and the ILC law with direct error feedback is explicitly obtained, A rigorous theorem is proposed, to prove the convergence of tracking error under ILC, The proposed methodology is illustrated on a typical batch reactor and the results show that the performance of trajectory tracking is gradually improved by the ILC. 展开更多
关键词 iterative learning control linear time-varying perturbation model batch process
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A Reliability Allocation Method of CNC Lathes Based on Copula Failure Correlation Model 被引量:8
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作者 Hao Wang Yi-Min Zhang Zhou Yang 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2018年第6期128-136,共9页
The current research of reliability allocation of CNC lathes always treat CNC lathes as independent series systems. However, CNC lathes are complex systems in the actual situation. Failure correlation is rarely consid... The current research of reliability allocation of CNC lathes always treat CNC lathes as independent series systems. However, CNC lathes are complex systems in the actual situation. Failure correlation is rarely considered when reliabil?ity allocation is conducted. In this paper, drawbacks of reliability model based on failure independence assumption are illustrated, after which, reliability model of CNC lathes considering failure correlation of subsystems is established based on Copula theory, which is an improvement of traditional reliability model of series systems. As the failure time of CNC lathes often obeys Weibull or exponential distribution, Gumbel Copula is selected to build correlation model. After that, a reliability allocation method considering failure correlation is analyzed based on the model established before. Reliability goal is set first and then failure rates are allocated to subsystems according to the allocation vector through solving the correlation model. Reliability allocation is conducted for t = 1. A real case of a CNC lathe and a numerical case are presented together to illustrate the advantages of the reliability model established consider?ing failure correlation and the corresponding allocation method. It shows that the model accords to facts and real working condition more, and failure rates allocated to all the subsystems are increased to some extent. This research proposes a reliability allocation method which takes failure correlation among subsystems of CNC lathes into consid?eration, and costs for design and manufacture could be decreased. 展开更多
关键词 CNC lathe copula Failure correlation Reliability model Reliability allocation
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Parameter Estimation of Time-Varying ARMA Model 被引量:3
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作者 王文华 韩力 王文星 《Journal of Beijing Institute of Technology》 EI CAS 2004年第2期131-134,共4页
The auto-regressive moving-average (ARMA) model with time-varying parameters is analyzed. The time-varying parameters are assumed to be a linear combination of a set of basis time-varying functions, and the feedbac... The auto-regressive moving-average (ARMA) model with time-varying parameters is analyzed. The time-varying parameters are assumed to be a linear combination of a set of basis time-varying functions, and the feedback linear estimation algorithm is used to estimate the time-varying parameters of the ARMA model. This algorithm includes 2 linear least squares estimations and a linear filter. The influence of the order of basis time-(varying) functions on parameters estimation is analyzed. The method has the advantage of simple, saving computation time and storage space. Theoretical analysis and experimental results show the validity of this method. 展开更多
关键词 auto-regressive moving-average (ARMA) model feedback linear estimation basis time-varying function spectral estimation
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Comparison of Cox proportional hazards model,Cox proportional hazards with time-varying coefficients model,and lognormal accelerated failure time model:Application in time to event analysis of melioidosis patients 被引量:1
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作者 Kamaruddin Mardhiah Nadiah Wan-Arfah +2 位作者 Nyi Nyi Naing Muhammad Radzi Abu Hassan Huan-Keat Chan 《Asian Pacific Journal of Tropical Medicine》 SCIE CAS 2022年第3期128-134,共7页
Objective:To compare the prognostic factors of mortality among melioidosis patients between lognormal accelerated failure time(AFT),Cox proportional hazards(PH),and Cox PH with time-varying coefficient(TVC)models.Meth... Objective:To compare the prognostic factors of mortality among melioidosis patients between lognormal accelerated failure time(AFT),Cox proportional hazards(PH),and Cox PH with time-varying coefficient(TVC)models.Methods:A retrospective study was conducted from 2014 to 2019 among 453 patients who were admitted to Hospital Sultanah Bahiyah,Kedah and Hospital Tuanku Fauziah,Perlis in Northern Malaysia due to confirmed-cultured melioidosis.The prognostic factors of mortality from melioidosis were obtained from AFT survival analysis,and Cox’s models and the findings were compared by using the goodness of fit methods.The analyses were done by using Stata SE version 14.0.Results:A total of 242 patients(53.4%)survived.In this study,the median survival time of melioidosis patients was 30.0 days(95%CI 0.0-60.9).Six significant prognostic factors were identified in the Cox PH model and Cox PH-TVC model.In AFT survival analysis,a total of seven significant prognostic factors were identified.The results were found to be only a slight difference between the identified prognostic factors among the models.AFT survival showed better results compared to Cox's models,with the lowest Akaike information criteria and best fitted Cox-snell residuals.Conclusions:AFT survival analysis provides more reliable results and can be used as an alternative statistical analysis for determining the prognostic factors of mortality in melioidosis patients in certain situations. 展开更多
关键词 Cox proportional hazards TIME-DEPENDENT time-varying Accelerated failure time survival analysis LOGNORMAL Parametric model TIME-TO-EVENT MELIOIDOSIS Mortality
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Deep learning-based time-varying channel estimation with basis expansion model for MIMO-OFDM system 被引量:1
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作者 HU Bo YANG Lihua +1 位作者 REN Lulu NIE Qian 《High Technology Letters》 EI CAS 2022年第3期288-294,共7页
For high-speed mobile MIMO-OFDM system,a low-complexity deep learning(DL) based timevarying channel estimation scheme is proposed.To reduce the number of estimated parameters,the basis expansion model(BEM) is employed... For high-speed mobile MIMO-OFDM system,a low-complexity deep learning(DL) based timevarying channel estimation scheme is proposed.To reduce the number of estimated parameters,the basis expansion model(BEM) is employed to model the time-varying channel,which converts the channel estimation into the estimation of the basis coefficient.Specifically,the initial basis coefficients are firstly used to train the neural network in an offline manner,and then the high-precision channel estimation can be obtained by small number of inputs.Moreover,the linear minimum mean square error(LMMSE) estimated channel is considered for the loss function in training phase,which makes the proposed method more practical.Simulation results show that the proposed method has a better performance and lower computational complexity compared with the available schemes,and it is robust to the fast time-varying channel in the high-speed mobile scenarios. 展开更多
关键词 MIMO-OFDM high-speed mobile time-varying channel deep learning(DL) basis expansion model(BEM)
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An imputation/copula-based stochastic individual tree growth model for mixed species Acadian forests: a case study using the Nova Scotia permanent sample plot network
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作者 John A. Kershaw Jr Aaron R. Weiskittel +1 位作者 Michael B. Lavigne Elizabeth McGarrigle 《Forest Ecosystems》 SCIE CSCD 2017年第4期251-263,共13页
Background: A novel approach to modelling individual tree growth dynamics is proposed. The approach combines multiple imputation and copula sampling to produce a stochastic individual tree growth and yield projection... Background: A novel approach to modelling individual tree growth dynamics is proposed. The approach combines multiple imputation and copula sampling to produce a stochastic individual tree growth and yield projection system. Methods: The Nova Scotia, Canada permanent sample plot network is used as a case study to develop and test the modelling approach. Predictions from this model are compared to predictions from the Acadian variant of the Forest Vegetation Simulator, a widely used statistical individual tree growth and yield model. Results: Diameter and height growth rates were predicted with error rates consistent with those produced using statistical models. Mortality and ingrowth error rates were higher than those observed for diameter and height, but also were within the bounds produced by traditional approaches for predicting these rates. Ingrowth species composition was very poorly predicted. The model was capable of reproducing a wide range of stand dynamic trajectories and in some cases reproduced trajectories that the statistical model was incapable of reproducing. Conclusions: The model has potential to be used as a benchmarking tool for evaluating statistical and process models and may provide a mechanism to separate signal from noise and improve our ability to analyze and learn from large regional datasets that often have underlying flaws in sample design. 展开更多
关键词 Nearest neighbor imputation copula sampling Individual tree growth model Mortality INGROWTH Mixed species stand development Acadian forests Nova Scotia
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Analytical Modeling and Mechanism Analysis of Time-Varying Excitation for Surface Defects in Rolling Element Bearings 被引量:1
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作者 Laihao Yang Yu Sun +2 位作者 Ruobin Sun Lixia Gao Xuefeng Chen 《Journal of Dynamics, Monitoring and Diagnostics》 2023年第2期89-101,共13页
Surface defects,including dents,spalls,and cracks,for rolling element bearings are the most common faults in rotating machinery.The accurate model for the time-varying excitation is the basis for the vibration mechani... Surface defects,including dents,spalls,and cracks,for rolling element bearings are the most common faults in rotating machinery.The accurate model for the time-varying excitation is the basis for the vibration mechanism analysis and fault feature extraction.However,in conventional investigations,this issue is not well and fully addressed from the perspective of theoretical analysis and physical derivation.In this study,an improved analytical model for time-varying displacement excitations(TVDEs)caused by surface defects is theoretically formulated.First and foremost,the physical mechanism for the effect of defect sizes on the physical process of rolling element-defect interaction is revealed.According to the physical interaction mechanism between the rolling element and different types of defects,the relationship between time-varying displacement pulse and defect sizes is further analytically derived.With the obtained time-varying displacement pulse,the dynamic model for the deep groove bearings considering the internal excitation caused by the surface defect is established.The nonlinear vibration responses and fault features induced by surface defects are analyzed using the proposed TVDE model.The results suggest that the presence of surface defects may result in the occurrence of the dual-impulse phenomenon,which can serve as indexes for surface-defect fault diagnosis. 展开更多
关键词 analytical model rolling bearings surface defects time-varying excitation vibration mechanism
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Time-varying gravity field model of Sichuan-Yunnan region based on the equivalent mass source model
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作者 Xiaozhen Hou Shi Chen +2 位作者 Linhai Wang Jiancheng Han Dong Ma 《Geodesy and Geodynamics》 EI CSCD 2023年第6期566-572,共7页
High-precision time-varying gravity field is an effective way to study the internal mass movement and understanding the spatio-temporal evolution process of the geodynamic system.Compared to the satellite gravity meas... High-precision time-varying gravity field is an effective way to study the internal mass movement and understanding the spatio-temporal evolution process of the geodynamic system.Compared to the satellite gravity measurement,the repeated terrestrial gravity observation can provide a more high-order signal related to the shallow crust and subsurface.However,the suitable and unified method for gravity model estimation is a key problem for further applications.In this study,we introduce the spherical hexahedron element to simulate the field source mass and forward model the change of gravity field located at the Sichuan-Yunnan region(99—104°E,23—29°N)in the four epochs from 2015 to 2017.Compared to the experimental results based on Slepian or spherical harmonics frequency domain method,this alternative approach is suitable for constructing the equivalent mass source model of regional-scale gravity data,by introducing the first-order smooth prior condition of gravity time-varying signal to suppress the high-frequency component of the signal.The results can provide a higher spatial resolution reference for regional gravity field modeling in the Sichuan-Yunnan region. 展开更多
关键词 Gravity change Equivalent source model time-varying gravity model Gravity field INVERSION
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An Improved Dynamic Modelling for Exploring Ball Bearing Vibrations from Time-Varying Oil Film 被引量:1
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作者 Minmin Xu Zhenzhen Song +3 位作者 Xiaoxi Ding Guoxing Li Yimin Shao James Xi Gu 《Journal of Dynamics, Monitoring and Diagnostics》 2022年第2期93-102,共10页
Bearings are key components in rotating machinery,which is widely used in many fields,such as CNC machines,wind turbines and induction machines.The increasingly harsh operation environment can lead to wear and tear on... Bearings are key components in rotating machinery,which is widely used in many fields,such as CNC machines,wind turbines and induction machines.The increasingly harsh operation environment can lead to wear and tear on raceways and reduce the precision and reliability of bearing or even machinery.Lubrication could relieve the wear to some degree,which is benefit to prolong the bearing’s life.Thus,investigation on the vibration responses under the influence of oil film is of great significance.However,for mechanism analysis,how to include the oil film into the bearing dynamic model affects the result and efficiency of solution.To address this problem,this study proposed a fast algorithm through load distribution and interpolation when calculating oil film stiffness and thickness during the solution of bearing vibration model.Analysis of oil film on vibration is carried out and a bearing test rig is designed to verify the proposed model.Numerical simulation result shows that rotational speed and load have vital effect on oil film and vibration.The experimental result is consistent with the simulation,which shows that the proposed model has a better performance on modeling bearing vibration and the method of considering oil film is reasonable. 展开更多
关键词 dynamic modeling fault diagnosis LUBRICATION rolling elements bearing time-varying oil film
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ICA Based Identification of Time-Varying Linear Causal Model
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作者 Hongxia Chen Jimin Ye 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2019年第4期32-40,共9页
Recently, several approaches have been proposed to discover the causality of the time-independent or fixed causal model. However, in many realistic applications, especially in economics and neuroscience, causality amo... Recently, several approaches have been proposed to discover the causality of the time-independent or fixed causal model. However, in many realistic applications, especially in economics and neuroscience, causality among variables might be time-varying. A time-varying linear causal model with non-Gaussian noise is considered and the estimation of the causal model from observational data is focused. Firstly, an independent component analysis(ICA) based two stage method is proposed to estimate the time-varying causal coefficients. It shows that, under appropriate assumptions, the time varying coefficients in the proposed model can be estimated by the proposed approach, and results of experiment on artificial data show the effectiveness of the proposed approach. And then, the granger causality test is used to ascertain the causal direction among the variables. Finally, the new approach is applied to the real stock data to identify the causality among three stock indices and the result is consistent with common sense. 展开更多
关键词 time-varying CAUSAL model independent component analysis(ICA) GRANGER CAUSALITY test CAUSALITY INFERENCE
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ADDITIVE HAZARDS MODEL WITH TIME-VARYING REGRESSION COEFFICIENTS
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作者 黄彬 《Acta Mathematica Scientia》 SCIE CSCD 2010年第4期1318-1326,共9页
This article discusses regression analysis of failure time under the additive hazards model, when the regression coefficients are time-varying. The regression coefficients are estimated locally based on the pseudo-sco... This article discusses regression analysis of failure time under the additive hazards model, when the regression coefficients are time-varying. The regression coefficients are estimated locally based on the pseudo-score function [12] in a window around each time point. The proposed method can be easily implemented, and the resulting estimators are shown to be consistent and asymptotically normal with easily estimated variances. The simulation studies show that our estimation procedure is reliable and useful. 展开更多
关键词 Additive hazards model time-varying coefficients weighted local pseudoscore function asymptotic property
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