We focus on the development of model selection criteria in linear mixed models. In particular, we propose the model selection criteria following the Mallows’ Conceptual Predictive Statistic (Cp) [1] [2] in linear mix...We focus on the development of model selection criteria in linear mixed models. In particular, we propose the model selection criteria following the Mallows’ Conceptual Predictive Statistic (Cp) [1] [2] in linear mixed models. When correlation exists between the observations in data, the normal Gauss discrepancy in univariate case is not appropriate to measure the distance between the true model and a candidate model. Instead, we define a marginal Gauss discrepancy which takes the correlation into account in the mixed models. The model selection criterion, marginal Cp, called MCp, serves as an asymptotically unbiased estimator of the expected marginal Gauss discrepancy. An improvement of MCp, called IMCp, is then derived and proved to be a more accurate estimator of the expected marginal Gauss discrepancy than MCp. The performance of the proposed criteria is investigated in a simulation study. The simulation results show that in small samples, the proposed criteria outperform the Akaike Information Criteria (AIC) [3] [4] and Bayesian Information Criterion (BIC) [5] in selecting the correct model;in large samples, their performance is competitive. Further, the proposed criteria perform significantly better for highly correlated response data than for weakly correlated data.展开更多
The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived usi...The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived using the optimally weighted combination theory and the minimum sum of logarithmic squared errors as the objective function.Two typical anchor bolt pull-out engineering cases were selected to compare the performance of the proposed model with those of existing ones.Results showed that the optimal combination model was suitable not only for the slow P-s curve but also for the steep P-s curve.Its accuracy and stable reliability,as well as its prediction capability classification,were better than those of the other prediction models.Therefore,the optimal combination model is an effective processing method for predicting the maximum pull-out load of anchor bolts according to measured data.展开更多
【目的】明晰地下储气库的热力学过程是压缩空气储能(compressed air energy storage,CAES)电站安全设计与运行调度的重要基础。【方法】现有地下储气库热力学模型在计算热量交换时,存在高压储气阶段热损失偏大和低压储气库阶段补热过...【目的】明晰地下储气库的热力学过程是压缩空气储能(compressed air energy storage,CAES)电站安全设计与运行调度的重要基础。【方法】现有地下储气库热力学模型在计算热量交换时,存在高压储气阶段热损失偏大和低压储气库阶段补热过多的不足。本文在全面分析地下储气库热力学模型理论基础合理性的前提下,先分析储气库热量计算偏差的形成根源;再提出改进模型。【结果】研究结果表明:现有的热力学计算解析模型忽略了CAES地下储气库在运行过程中温度分布的不均匀性,这种温度分布的不均匀导致储气室洞壁与压缩空气之间的对流换热模型失真,导致温度计算结果偏差大。考虑混合对流换热的改进模型二可以较好地解决储气阶段温度计算结果与真实结果之间偏差过大的问题。算例分析证明了改进模型二的合理性。【结论】本文的改进模型二可为CAES地下储气库容积优化设计与效率分析提供计算依据。展开更多
为提高智能网联(connected and automated,CA)卡车、小车及人工驾驶卡车、小车的混合流道路通行能力,提出基于排强度和渗透率的CA车辆单独编队和合作编队策略.分别设计两种策略下混合流车辆跟驰模式,推导出基于改进Markov模型,涵盖CA车...为提高智能网联(connected and automated,CA)卡车、小车及人工驾驶卡车、小车的混合流道路通行能力,提出基于排强度和渗透率的CA车辆单独编队和合作编队策略.分别设计两种策略下混合流车辆跟驰模式,推导出基于改进Markov模型,涵盖CA车辆渗透率和排强度的车辆状态转移概率;分析两种策略下CA车辆队列分布,建立各策略下的混合流道路容量模型,并通过理论证明和仿真实验予以验证.结果表明,与不编队策略相比,两种策略下道路容量分别提高1.23%~49.62%和1.47%~60.34%,合作编队策略与单独编队策略相比能将道路容量再提高11%;当CA车辆渗透率大于50%和排强度大于0时,编队策略对道路容量的提升效果更显著,容量能提高13.27%~60.34%;单独编队策略下CA小车和CA卡车最大队列规模分别为8辆和6辆,合作编队下CA车辆最大队列规模为8辆.展开更多
文摘We focus on the development of model selection criteria in linear mixed models. In particular, we propose the model selection criteria following the Mallows’ Conceptual Predictive Statistic (Cp) [1] [2] in linear mixed models. When correlation exists between the observations in data, the normal Gauss discrepancy in univariate case is not appropriate to measure the distance between the true model and a candidate model. Instead, we define a marginal Gauss discrepancy which takes the correlation into account in the mixed models. The model selection criterion, marginal Cp, called MCp, serves as an asymptotically unbiased estimator of the expected marginal Gauss discrepancy. An improvement of MCp, called IMCp, is then derived and proved to be a more accurate estimator of the expected marginal Gauss discrepancy than MCp. The performance of the proposed criteria is investigated in a simulation study. The simulation results show that in small samples, the proposed criteria outperform the Akaike Information Criteria (AIC) [3] [4] and Bayesian Information Criterion (BIC) [5] in selecting the correct model;in large samples, their performance is competitive. Further, the proposed criteria perform significantly better for highly correlated response data than for weakly correlated data.
基金The National Natural Science Foundation of China(No.51778485).
文摘The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived using the optimally weighted combination theory and the minimum sum of logarithmic squared errors as the objective function.Two typical anchor bolt pull-out engineering cases were selected to compare the performance of the proposed model with those of existing ones.Results showed that the optimal combination model was suitable not only for the slow P-s curve but also for the steep P-s curve.Its accuracy and stable reliability,as well as its prediction capability classification,were better than those of the other prediction models.Therefore,the optimal combination model is an effective processing method for predicting the maximum pull-out load of anchor bolts according to measured data.
文摘【目的】明晰地下储气库的热力学过程是压缩空气储能(compressed air energy storage,CAES)电站安全设计与运行调度的重要基础。【方法】现有地下储气库热力学模型在计算热量交换时,存在高压储气阶段热损失偏大和低压储气库阶段补热过多的不足。本文在全面分析地下储气库热力学模型理论基础合理性的前提下,先分析储气库热量计算偏差的形成根源;再提出改进模型。【结果】研究结果表明:现有的热力学计算解析模型忽略了CAES地下储气库在运行过程中温度分布的不均匀性,这种温度分布的不均匀导致储气室洞壁与压缩空气之间的对流换热模型失真,导致温度计算结果偏差大。考虑混合对流换热的改进模型二可以较好地解决储气阶段温度计算结果与真实结果之间偏差过大的问题。算例分析证明了改进模型二的合理性。【结论】本文的改进模型二可为CAES地下储气库容积优化设计与效率分析提供计算依据。
文摘为提高智能网联(connected and automated,CA)卡车、小车及人工驾驶卡车、小车的混合流道路通行能力,提出基于排强度和渗透率的CA车辆单独编队和合作编队策略.分别设计两种策略下混合流车辆跟驰模式,推导出基于改进Markov模型,涵盖CA车辆渗透率和排强度的车辆状态转移概率;分析两种策略下CA车辆队列分布,建立各策略下的混合流道路容量模型,并通过理论证明和仿真实验予以验证.结果表明,与不编队策略相比,两种策略下道路容量分别提高1.23%~49.62%和1.47%~60.34%,合作编队策略与单独编队策略相比能将道路容量再提高11%;当CA车辆渗透率大于50%和排强度大于0时,编队策略对道路容量的提升效果更显著,容量能提高13.27%~60.34%;单独编队策略下CA小车和CA卡车最大队列规模分别为8辆和6辆,合作编队下CA车辆最大队列规模为8辆.
