Reliability and remaining useful life(RUL)estimation for a satellite rechargeable lithium battery(RLB)are significant for prognostic and health management(PHM).A novel Bayesian framework is proposed to do reliability ...Reliability and remaining useful life(RUL)estimation for a satellite rechargeable lithium battery(RLB)are significant for prognostic and health management(PHM).A novel Bayesian framework is proposed to do reliability analysis by synthesizing multisource data,including bivariate degradation data and lifetime data.Bivariate degradation means that there are two degraded performance characteristics leading to the failure of the system.First,linear Wiener process and Frank Copula function are used to model the dependent degradation processes of the RLB's temperature and discharge voltage.Next,the Bayesian method,in combination with Markov Chain Monte Carlo(MCMC)simulations,is provided to integrate limited bivariate degradation data with other congeneric RLBs'lifetime data.Then reliability evaluation and RUL prediction are carried out for PHM.A simulation study demonstrates that due to the data fusion,parameter estimations and predicted RUL obtained from our model are more precise than models only using degradation data or ignoring the dependency of different degradation processes.Finally,a practical case study of a satellite RLB verifies the usability of the model.展开更多
The traditional least squares support vector regression（LS-SVR）model,using cross validation to determine the regularization parameter and kernel parameter,is time-consuming.We propose a Bayesian evidence framework t...The traditional least squares support vector regression（LS-SVR）model,using cross validation to determine the regularization parameter and kernel parameter,is time-consuming.We propose a Bayesian evidence framework to infer the LS-SVR model parameters.Three levels Bayesian inferences are used to determine the model parameters,regularization hyper-parameters and tune the nuclear parameters by model comparison.On this basis,we established Bayesian LS-SVR time-series gas forecasting models and provide steps for the algorithm.The gas outburst data of a Hebi 10th mine working face is used to validate the model.The optimal embedding dimension and delay time of the time series were obtained by the smallest differential entropy method.Finally,within a MATLAB7.1 environment,we used actual coal gas data to compare the traditional LS-SVR and the Bayesian LS-SVR with LS-SVMlab1.5 Toolbox simulation.The results show that the Bayesian framework of an LS-SVR significantly improves the speed and accuracy of the forecast.展开更多
Fluid identification and anisotropic parameters characterization are crucial for shale reservoir exploration and development.However,the anisotropic reflection coefficient equation,based on the transverse isotropy wit...Fluid identification and anisotropic parameters characterization are crucial for shale reservoir exploration and development.However,the anisotropic reflection coefficient equation,based on the transverse isotropy with a vertical axis of symmetry(VTI)medium assumption,involves numerous parameters to be inverted.This complexity reduces its stability and impacts the accuracy of seismic amplitude variation with offset(AVO)inversion results.In this study,a novel anisotropic equation that includes the fluid term and Thomsen anisotropic parameters is rewritten,which reduces the equation's dimensionality and increases its stability.Additionally,the traditional Markov Chain Monte Carlo(MCMC)inversion algorithm exhibits a high rejection rate for random samples and relies on known parameter distributions such as the Gaussian distribution,limiting the algorithm's convergence and sample randomness.To address these limitations and evaluate the uncertainty of AVO inversion,the IADR-Gibbs algorithm is proposed,which incorporates the Independent Adaptive Delayed Rejection(IADR)algorithm with the Gibbs sampling algorithm.Grounded in Bayesian theory,the new algorithm introduces support points to construct a proposal distribution of non-parametric distribution and reselects the rejected samples according to the Delayed Rejection(DR)strategy.Rejected samples are then added to the support points to update the proposal distribution function adaptively.The equation rewriting method and the IADR-Gibbs algorithm improve the accuracy and robustness of AVO inversion.The effectiveness and applicability of the proposed method are validated through synthetic gather tests and practical data applications.展开更多
In the paper, an iterative method is presented to the optimal control of batch processes. Generally it is very difficult to acquire an accurate mechanistic model for a batch process. Because support vector machine is ...In the paper, an iterative method is presented to the optimal control of batch processes. Generally it is very difficult to acquire an accurate mechanistic model for a batch process. Because support vector machine is powerful for the problems characterized by small samples, nonlinearity, high dimension and local minima, support vector regression models are developed for the optimal control of batch processes where end-point properties are required. The model parameters are selected within the Bayesian evidence framework. Based on the model, an iterative method is used to exploit the repetitive nature of batch processes to determine the optimal operating policy. Numerical simulation shows that the iterative optimal control can improve the process performance through iterations.展开更多
The command and control（C2） is a decision-making process based on human cognition,which contains operational,physical,and human characteristics,so it takes on uncertainty and complexity.As a decision support approac...The command and control（C2） is a decision-making process based on human cognition,which contains operational,physical,and human characteristics,so it takes on uncertainty and complexity.As a decision support approach,Bayesian networks（BNs） provide a framework in which a decision is made by combining the experts＇ knowledge and the specific data.In addition,an expert system represented by human cognitive framework is adopted to express the real-time decision-making process of the decision maker.The combination of the Bayesian decision support and human cognitive framework in the C2 of a specific application field is modeled and executed by colored Petri nets（CPNs）,and the consequences of execution manifest such combination can perfectly present the decision-making process in C2.展开更多
Seismic inversion is a highly ill-posed problem, due to many factors such as the limited seismic frequency bandwidth and inappropriate forward modeling. To obtain a unique solution, some smoothing constraints, e.g., t...Seismic inversion is a highly ill-posed problem, due to many factors such as the limited seismic frequency bandwidth and inappropriate forward modeling. To obtain a unique solution, some smoothing constraints, e.g., the Tikhonov regularization are usually applied. The Tikhonov method can maintain a global smooth solution, but cause a fuzzy structure edge. In this paper we use Huber-Markov random-field edge protection method in the procedure of inverting three parameters, P-velocity, S-velocity and density. The method can avoid blurring the structure edge and resist noise. For the parameter to be inverted, the Huber- Markov random-field constructs a neighborhood system, which further acts as the vertical and lateral constraints. We use a quadratic Huber edge penalty function within the layer to suppress noise and a linear one on the edges to avoid a fuzzy result. The effectiveness of our method is proved by inverting the synthetic data without and with noises. The relationship between the adopted constraints and the inversion results is analyzed as well.展开更多
This study seeks to investigate the variations associated with lane lateral locations and days of the week in the stochastic and dynamic transition of traffic regimes(DTTR).In the proposed analysis,hierarchical regres...This study seeks to investigate the variations associated with lane lateral locations and days of the week in the stochastic and dynamic transition of traffic regimes(DTTR).In the proposed analysis,hierarchical regression models fitted using Bayesian frameworks were used to calibrate the transition probabilities that describe the DTTR.Datasets of two sites on a freeway facility located in Jacksonville,Florida,were selected for the analysis.The traffic speed thresholds to define traffic regimes were estimated using the Gaussian mixture model(GMM).The GMM revealed that two and three regimes were adequate mixture components for estimating the traffic speed distributions for Site 1 and 2 datasets,respectively.The results of hierarchical regression models show that there is considerable evidence that there are heterogeneity characteristics in the DTTR associated with lateral lane locations.In particular,the hierarchical regressions reveal that the breakdown process is more affected by the variations compared to other evaluated transition processes with the estimated intra-class correlation(ICC)of about 73%.The transition from congestion on-set/dissolution(COD)to the congested regime is estimated with the highest ICC of 49.4%in the three-regime model,and the lowest ICC of 1%was observed on the transition from the congested to COD regime.On the other hand,different days of the week are not found to contribute to the variations(the highest ICC was 1.44%)on the DTTR.These findings can be used in developing effective congestion countermeasures,particularly in the application of intelligent transportation systems,such as dynamic lane-management strategies.展开更多
目的系统评价疏肝利胆法中成药治疗慢性胆囊炎的疗效与安全性,为临床治疗决策提供循证依据。方法计算机检索中国知网、万方、维普、中国生物医学文献服务系统、PubMed、Embase及Web of Science等数据库中,关于疏肝利胆法中成药治疗慢性...目的系统评价疏肝利胆法中成药治疗慢性胆囊炎的疗效与安全性,为临床治疗决策提供循证依据。方法计算机检索中国知网、万方、维普、中国生物医学文献服务系统、PubMed、Embase及Web of Science等数据库中,关于疏肝利胆法中成药治疗慢性胆囊炎的随机对照试验(Randomized controlled trial,RCT),检索时限为自建库起至2025年1月12日。由2名研究员根据设定好的标准进行文献筛选、数据提取及文献质量评价。应用R 4.4.3软件及“BUGSnet”程序包进行贝叶斯网状Meta分析(Network meta-analysis,NMA)。结果最终纳入39篇RCTs,包含3412例慢性胆囊炎患者,涉及消石利胆胶囊、消炎利胆片、胆石利通片、胆舒胶囊、胆宁片、八宝丹胶囊、舒胆胶囊/片、金胆片、十味蒂达胶囊等9种不同疏肝利胆法中成药。NMA结果显示:在综合有效率方面,八宝丹胶囊[累积排序概率曲线下面积(Surface under the cumulative ranking curve,SUCRA),SUCRA=98.61%]、消石利胆胶囊联合西医常规治疗(SUCRA=78.95%)疗效明显;在疼痛缓解方面,采用视觉模拟量表(Visual analog scale,VAS)、疼痛评级指数(Pain rating index,PRI)和现有疼痛强度(Present pain intensity,PPI)评分作为评价指标,结果显示消石利胆胶囊单用(VAS-SUCRA=86.34%、PRI-SUCRA=99.38%)及联合西医常规治疗(PPI-SUCRA=79.39%)镇痛效果突出;在抗炎、降低白细胞介素-6(Interleukin-6,IL-6)水平方面,消石利胆胶囊联合西医常规治疗(SUCRA=92.92%)与胆舒胶囊联合西医常规治疗(SUCRA=55.79%)疗效排序靠前;在安全性方面,八宝丹胶囊(不良反应A-SUCRA=93.92%)、消石利胆胶囊(不良反应B-SUCRA=96.24%)不良反应发生率最低,且单一制剂安全性优于联合方案。敏感性分析显示,剔除异常研究后核心结论无实质性改变(SUCRA波动<6%)。结论疏肝利胆法中成药治疗慢性胆囊炎在综合疗效、疼痛缓解、抗炎及安全性方面表现突出,其中八宝丹胶囊、消石利胆胶囊(单用或联合西医常规治疗)为优选方案。展开更多
Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and ideal...Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and idealized models increases the uncertainties of the inversion result. Thus, we propose an inversion method that is different from traditional statistical rock physics modeling. First, we use deterministic and stochastic rock physics models considering the uncertainties of elastic parameters obtained by prestack seismic inversion and introduce weighting coefficients to establish a weighted statistical relation between reservoir and elastic parameters. Second, based on the weighted statistical relation, we use Markov chain Monte Carlo simulations to generate the random joint distribution space of reservoir and elastic parameters that serves as a sample solution space of an objective function. Finally, we propose a fast solution criterion to maximize the posterior probability density and obtain reservoir parameters. The method has high efficiency and application potential.展开更多
基金Project(71371182) supported by the National Natural Science Foundation of China
文摘Reliability and remaining useful life(RUL)estimation for a satellite rechargeable lithium battery(RLB)are significant for prognostic and health management(PHM).A novel Bayesian framework is proposed to do reliability analysis by synthesizing multisource data,including bivariate degradation data and lifetime data.Bivariate degradation means that there are two degraded performance characteristics leading to the failure of the system.First,linear Wiener process and Frank Copula function are used to model the dependent degradation processes of the RLB's temperature and discharge voltage.Next,the Bayesian method,in combination with Markov Chain Monte Carlo(MCMC)simulations,is provided to integrate limited bivariate degradation data with other congeneric RLBs'lifetime data.Then reliability evaluation and RUL prediction are carried out for PHM.A simulation study demonstrates that due to the data fusion,parameter estimations and predicted RUL obtained from our model are more precise than models only using degradation data or ignoring the dependency of different degradation processes.Finally,a practical case study of a satellite RLB verifies the usability of the model.
基金Financial support for this work,provided by the National Natural Science Foundation of China(No.60974126)the Natural Science Foundation of Jiangsu Province(No.BK2009094)
文摘The traditional least squares support vector regression（LS-SVR）model,using cross validation to determine the regularization parameter and kernel parameter,is time-consuming.We propose a Bayesian evidence framework to infer the LS-SVR model parameters.Three levels Bayesian inferences are used to determine the model parameters,regularization hyper-parameters and tune the nuclear parameters by model comparison.On this basis,we established Bayesian LS-SVR time-series gas forecasting models and provide steps for the algorithm.The gas outburst data of a Hebi 10th mine working face is used to validate the model.The optimal embedding dimension and delay time of the time series were obtained by the smallest differential entropy method.Finally,within a MATLAB7.1 environment,we used actual coal gas data to compare the traditional LS-SVR and the Bayesian LS-SVR with LS-SVMlab1.5 Toolbox simulation.The results show that the Bayesian framework of an LS-SVR significantly improves the speed and accuracy of the forecast.
基金the sponsorship of the Key Technology for Geophysical Prediction of Ultra-Deep Carbonate Reservoirs(P24240)the National Natural Science Foundation of China(U24B2020)the National Science and Technology Major Project of China for New Oil and Gas Exploration and Development(Grant No.2024ZD1400102)。
文摘Fluid identification and anisotropic parameters characterization are crucial for shale reservoir exploration and development.However,the anisotropic reflection coefficient equation,based on the transverse isotropy with a vertical axis of symmetry(VTI)medium assumption,involves numerous parameters to be inverted.This complexity reduces its stability and impacts the accuracy of seismic amplitude variation with offset(AVO)inversion results.In this study,a novel anisotropic equation that includes the fluid term and Thomsen anisotropic parameters is rewritten,which reduces the equation's dimensionality and increases its stability.Additionally,the traditional Markov Chain Monte Carlo(MCMC)inversion algorithm exhibits a high rejection rate for random samples and relies on known parameter distributions such as the Gaussian distribution,limiting the algorithm's convergence and sample randomness.To address these limitations and evaluate the uncertainty of AVO inversion,the IADR-Gibbs algorithm is proposed,which incorporates the Independent Adaptive Delayed Rejection(IADR)algorithm with the Gibbs sampling algorithm.Grounded in Bayesian theory,the new algorithm introduces support points to construct a proposal distribution of non-parametric distribution and reselects the rejected samples according to the Delayed Rejection(DR)strategy.Rejected samples are then added to the support points to update the proposal distribution function adaptively.The equation rewriting method and the IADR-Gibbs algorithm improve the accuracy and robustness of AVO inversion.The effectiveness and applicability of the proposed method are validated through synthetic gather tests and practical data applications.
基金Project supported by the National Natural Science Foundation of China(Grant No.60504033)
文摘In the paper, an iterative method is presented to the optimal control of batch processes. Generally it is very difficult to acquire an accurate mechanistic model for a batch process. Because support vector machine is powerful for the problems characterized by small samples, nonlinearity, high dimension and local minima, support vector regression models are developed for the optimal control of batch processes where end-point properties are required. The model parameters are selected within the Bayesian evidence framework. Based on the model, an iterative method is used to exploit the repetitive nature of batch processes to determine the optimal operating policy. Numerical simulation shows that the iterative optimal control can improve the process performance through iterations.
基金supported by the National Natural Science Foundation of China (60874068)
文摘The command and control（C2） is a decision-making process based on human cognition,which contains operational,physical,and human characteristics,so it takes on uncertainty and complexity.As a decision support approach,Bayesian networks（BNs） provide a framework in which a decision is made by combining the experts＇ knowledge and the specific data.In addition,an expert system represented by human cognitive framework is adopted to express the real-time decision-making process of the decision maker.The combination of the Bayesian decision support and human cognitive framework in the C2 of a specific application field is modeled and executed by colored Petri nets（CPNs）,and the consequences of execution manifest such combination can perfectly present the decision-making process in C2.
基金supported by the National Basic Research Program of China(973 Program)(No.2013CB228603)National Science and Technology major projects(No.2011ZX05024 and 2011ZX05010)the National Natural Science Foundation of China(No.41174119)
文摘Seismic inversion is a highly ill-posed problem, due to many factors such as the limited seismic frequency bandwidth and inappropriate forward modeling. To obtain a unique solution, some smoothing constraints, e.g., the Tikhonov regularization are usually applied. The Tikhonov method can maintain a global smooth solution, but cause a fuzzy structure edge. In this paper we use Huber-Markov random-field edge protection method in the procedure of inverting three parameters, P-velocity, S-velocity and density. The method can avoid blurring the structure edge and resist noise. For the parameter to be inverted, the Huber- Markov random-field constructs a neighborhood system, which further acts as the vertical and lateral constraints. We use a quadratic Huber edge penalty function within the layer to suppress noise and a linear one on the edges to avoid a fuzzy result. The effectiveness of our method is proved by inverting the synthetic data without and with noises. The relationship between the adopted constraints and the inversion results is analyzed as well.
文摘This study seeks to investigate the variations associated with lane lateral locations and days of the week in the stochastic and dynamic transition of traffic regimes(DTTR).In the proposed analysis,hierarchical regression models fitted using Bayesian frameworks were used to calibrate the transition probabilities that describe the DTTR.Datasets of two sites on a freeway facility located in Jacksonville,Florida,were selected for the analysis.The traffic speed thresholds to define traffic regimes were estimated using the Gaussian mixture model(GMM).The GMM revealed that two and three regimes were adequate mixture components for estimating the traffic speed distributions for Site 1 and 2 datasets,respectively.The results of hierarchical regression models show that there is considerable evidence that there are heterogeneity characteristics in the DTTR associated with lateral lane locations.In particular,the hierarchical regressions reveal that the breakdown process is more affected by the variations compared to other evaluated transition processes with the estimated intra-class correlation(ICC)of about 73%.The transition from congestion on-set/dissolution(COD)to the congested regime is estimated with the highest ICC of 49.4%in the three-regime model,and the lowest ICC of 1%was observed on the transition from the congested to COD regime.On the other hand,different days of the week are not found to contribute to the variations(the highest ICC was 1.44%)on the DTTR.These findings can be used in developing effective congestion countermeasures,particularly in the application of intelligent transportation systems,such as dynamic lane-management strategies.
文摘目的系统评价疏肝利胆法中成药治疗慢性胆囊炎的疗效与安全性,为临床治疗决策提供循证依据。方法计算机检索中国知网、万方、维普、中国生物医学文献服务系统、PubMed、Embase及Web of Science等数据库中,关于疏肝利胆法中成药治疗慢性胆囊炎的随机对照试验(Randomized controlled trial,RCT),检索时限为自建库起至2025年1月12日。由2名研究员根据设定好的标准进行文献筛选、数据提取及文献质量评价。应用R 4.4.3软件及“BUGSnet”程序包进行贝叶斯网状Meta分析(Network meta-analysis,NMA)。结果最终纳入39篇RCTs,包含3412例慢性胆囊炎患者,涉及消石利胆胶囊、消炎利胆片、胆石利通片、胆舒胶囊、胆宁片、八宝丹胶囊、舒胆胶囊/片、金胆片、十味蒂达胶囊等9种不同疏肝利胆法中成药。NMA结果显示:在综合有效率方面,八宝丹胶囊[累积排序概率曲线下面积(Surface under the cumulative ranking curve,SUCRA),SUCRA=98.61%]、消石利胆胶囊联合西医常规治疗(SUCRA=78.95%)疗效明显;在疼痛缓解方面,采用视觉模拟量表(Visual analog scale,VAS)、疼痛评级指数(Pain rating index,PRI)和现有疼痛强度(Present pain intensity,PPI)评分作为评价指标,结果显示消石利胆胶囊单用(VAS-SUCRA=86.34%、PRI-SUCRA=99.38%)及联合西医常规治疗(PPI-SUCRA=79.39%)镇痛效果突出;在抗炎、降低白细胞介素-6(Interleukin-6,IL-6)水平方面,消石利胆胶囊联合西医常规治疗(SUCRA=92.92%)与胆舒胶囊联合西医常规治疗(SUCRA=55.79%)疗效排序靠前;在安全性方面,八宝丹胶囊(不良反应A-SUCRA=93.92%)、消石利胆胶囊(不良反应B-SUCRA=96.24%)不良反应发生率最低,且单一制剂安全性优于联合方案。敏感性分析显示,剔除异常研究后核心结论无实质性改变(SUCRA波动<6%)。结论疏肝利胆法中成药治疗慢性胆囊炎在综合疗效、疼痛缓解、抗炎及安全性方面表现突出,其中八宝丹胶囊、消石利胆胶囊(单用或联合西医常规治疗)为优选方案。
基金supported by the National Science and Technology Major Project(No.2011 ZX05007-006)the 973 Program of China(No.2013CB228604)the Major Project of Petrochina(No.2014B-0610)
文摘Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and idealized models increases the uncertainties of the inversion result. Thus, we propose an inversion method that is different from traditional statistical rock physics modeling. First, we use deterministic and stochastic rock physics models considering the uncertainties of elastic parameters obtained by prestack seismic inversion and introduce weighting coefficients to establish a weighted statistical relation between reservoir and elastic parameters. Second, based on the weighted statistical relation, we use Markov chain Monte Carlo simulations to generate the random joint distribution space of reservoir and elastic parameters that serves as a sample solution space of an objective function. Finally, we propose a fast solution criterion to maximize the posterior probability density and obtain reservoir parameters. The method has high efficiency and application potential.
