This study presents a Bayesian methodology for de- signing step stress accelerated degradation testing （SSADT） and its application to batteries. First, the simulation-based Bayesian de- sign framework for SSADT is p...This study presents a Bayesian methodology for de- signing step stress accelerated degradation testing （SSADT） and its application to batteries. First, the simulation-based Bayesian de- sign framework for SSADT is presented. Then, by considering his- torical data, specific optimal objectives oriented Kullback-Leibler （KL） divergence is established. A numerical example is discussed to illustrate the design approach. It is assumed that the degrada- tion model （or process） follows a drift Brownian motion; the accele- ration model follows Arrhenius equation; and the corresponding parameters follow normal and Gamma prior distributions. Using the Markov Chain Monte Carlo （MCMC） method and WinBUGS software, the comparison shows that KL divergence is better than quadratic loss for optimal criteria. Further, the effect of simulation outiiers on the optimization plan is analyzed and the preferred sur- face fitting algorithm is chosen. At the end of the paper, a NASA lithium-ion battery dataset is used as historical information and the KL divergence oriented Bayesian design is compared with maxi- mum likelihood theory oriented locally optimal design. The results show that the proposed method can provide a much better testing plan for this engineering application.展开更多
As only a little information can be obtained from torpedo's lake and sea tests,and the torpedo's life does not distribute typically. If conventional methods are used to convert the environment factor for torpe...As only a little information can be obtained from torpedo's lake and sea tests,and the torpedo's life does not distribute typically. If conventional methods are used to convert the environment factor for torpedo's lake and sea tests,their results can not reflect the actual conditions. A conversion model of the environment factor for torpedo's lake and sea tests is set up based on the GM(1,2) model of the grey system theory. For the merit of the grey system,the problem of uncertain life distributions and few samples can be solved. The calculation results show that the method is easy,realistic and high precise.展开更多
目的编制脑卒中患者照顾者倦怠量表(burnout scale of stroke patients’caregivers,BSSPCs),并进行信效度检验,为脑卒中患者照顾者倦怠测评提供工具。方法在前期构建的脑卒中患者主要照顾者倦怠概念框架及文献分析的基础上,借鉴职业倦...目的编制脑卒中患者照顾者倦怠量表(burnout scale of stroke patients’caregivers,BSSPCs),并进行信效度检验,为脑卒中患者照顾者倦怠测评提供工具。方法在前期构建的脑卒中患者主要照顾者倦怠概念框架及文献分析的基础上,借鉴职业倦怠量表,构建条目池;通过专家咨询法及预调查,形成BSSPCs初稿;2022年7月至2023年1月,采用便利抽样法选取银川市和吴忠市5所医院康复科收治的506名脑卒中患者照顾者进行调查,应用经典测量理论(classical test theory,CTT)和项目反应理论(item response theory,IRT)对量表进行测量学评价。结果CTT结果提示存在6个条目不满足统计学要求,IRT结果显示共6个条目不符合难度、区分度或信息量的筛选标准,最终形成的BSSPCs包括角色倦怠、生理倦怠、心理倦怠和社交倦怠4个维度共24个条目。结论BSSPCs的编制过程严谨,各项心理学测量指标比较满意,为量化照顾者倦怠和开展后续研究提供了工具支持。展开更多
变异函数量化了空间2点地质属性的变异性,对地质统计分析至关重要。当地质数据随空间坐标呈现趋势变化时,正确选择和估计变异函数十分困难。为实现变异函数的模型选择和参数估计,提出了基于贝叶斯理论的变异函数选择方法,采用拉普拉斯...变异函数量化了空间2点地质属性的变异性,对地质统计分析至关重要。当地质数据随空间坐标呈现趋势变化时,正确选择和估计变异函数十分困难。为实现变异函数的模型选择和参数估计,提出了基于贝叶斯理论的变异函数选择方法,采用拉普拉斯近似方法将后验概率分布近似为高斯分布。首先计算出参数的后验概率分布,随后分别计算每个备选变异函数的贝叶斯模型证据,以确定最优模型。探讨了3种模型选择方法在变异函数选择中的适用性,包括贝叶斯模型证据(BME)、Akaike information criterion(AIC)识别准则和Bayesian information criterion(BIC)识别准则。通过实测静力触探试验的锥端阻力数据,说明了该方法,并从模型拟合度和复杂度罚值2个方面比较3种方法在变异函数模型选择中的差异性。研究表明,给定试验数据条件下,BME能够合理地考虑变异函数的拟合度和复杂性;而AIC和BIC识别准则在模型参数个数相同时,仅能反映不同变异函数的拟合度差异,因此,在这种情况下推荐采用BME选择变异函数。本研究方法能够在考虑趋势项参数条件下合理地选择地质统计学变异函数,所选最优变异函数与试验变异函数较一致,为地质统计学分析提供了有效的参考。展开更多
基金supported by the National Natural Science Foundation of China(61104182)
文摘This study presents a Bayesian methodology for de- signing step stress accelerated degradation testing （SSADT） and its application to batteries. First, the simulation-based Bayesian de- sign framework for SSADT is presented. Then, by considering his- torical data, specific optimal objectives oriented Kullback-Leibler （KL） divergence is established. A numerical example is discussed to illustrate the design approach. It is assumed that the degrada- tion model （or process） follows a drift Brownian motion; the accele- ration model follows Arrhenius equation; and the corresponding parameters follow normal and Gamma prior distributions. Using the Markov Chain Monte Carlo （MCMC） method and WinBUGS software, the comparison shows that KL divergence is better than quadratic loss for optimal criteria. Further, the effect of simulation outiiers on the optimization plan is analyzed and the preferred sur- face fitting algorithm is chosen. At the end of the paper, a NASA lithium-ion battery dataset is used as historical information and the KL divergence oriented Bayesian design is compared with maxi- mum likelihood theory oriented locally optimal design. The results show that the proposed method can provide a much better testing plan for this engineering application.
文摘As only a little information can be obtained from torpedo's lake and sea tests,and the torpedo's life does not distribute typically. If conventional methods are used to convert the environment factor for torpedo's lake and sea tests,their results can not reflect the actual conditions. A conversion model of the environment factor for torpedo's lake and sea tests is set up based on the GM(1,2) model of the grey system theory. For the merit of the grey system,the problem of uncertain life distributions and few samples can be solved. The calculation results show that the method is easy,realistic and high precise.
文摘目的编制脑卒中患者照顾者倦怠量表(burnout scale of stroke patients’caregivers,BSSPCs),并进行信效度检验,为脑卒中患者照顾者倦怠测评提供工具。方法在前期构建的脑卒中患者主要照顾者倦怠概念框架及文献分析的基础上,借鉴职业倦怠量表,构建条目池;通过专家咨询法及预调查,形成BSSPCs初稿;2022年7月至2023年1月,采用便利抽样法选取银川市和吴忠市5所医院康复科收治的506名脑卒中患者照顾者进行调查,应用经典测量理论(classical test theory,CTT)和项目反应理论(item response theory,IRT)对量表进行测量学评价。结果CTT结果提示存在6个条目不满足统计学要求,IRT结果显示共6个条目不符合难度、区分度或信息量的筛选标准,最终形成的BSSPCs包括角色倦怠、生理倦怠、心理倦怠和社交倦怠4个维度共24个条目。结论BSSPCs的编制过程严谨,各项心理学测量指标比较满意,为量化照顾者倦怠和开展后续研究提供了工具支持。
文摘变异函数量化了空间2点地质属性的变异性,对地质统计分析至关重要。当地质数据随空间坐标呈现趋势变化时,正确选择和估计变异函数十分困难。为实现变异函数的模型选择和参数估计,提出了基于贝叶斯理论的变异函数选择方法,采用拉普拉斯近似方法将后验概率分布近似为高斯分布。首先计算出参数的后验概率分布,随后分别计算每个备选变异函数的贝叶斯模型证据,以确定最优模型。探讨了3种模型选择方法在变异函数选择中的适用性,包括贝叶斯模型证据(BME)、Akaike information criterion(AIC)识别准则和Bayesian information criterion(BIC)识别准则。通过实测静力触探试验的锥端阻力数据,说明了该方法,并从模型拟合度和复杂度罚值2个方面比较3种方法在变异函数模型选择中的差异性。研究表明,给定试验数据条件下,BME能够合理地考虑变异函数的拟合度和复杂性;而AIC和BIC识别准则在模型参数个数相同时,仅能反映不同变异函数的拟合度差异,因此,在这种情况下推荐采用BME选择变异函数。本研究方法能够在考虑趋势项参数条件下合理地选择地质统计学变异函数,所选最优变异函数与试验变异函数较一致,为地质统计学分析提供了有效的参考。
