基于ARIMA线性时间序列的埋地输油管道剩余寿命预测

针对埋地输油管道剩余寿命预测问题,构建基于ARIMA线性时间序列的埋地输油管道剩余寿命预测模型,并对输油管道剩余寿命进行预测。结果表明：基于ARIMA模型预测出该段管道的剩余寿命为27年,与专业的压力实验计算出的剩余使用寿命28年最为接近,与其他模型对比研究,ARIMA模型更为准确地预测出管道剩余寿命。     

注汽锅炉高温炉管有限元分析剩余寿命

利用有限元法对危险段炉管进行详细的应力分析,运用序贯热—应力藕合得出总应力场分布,并以此为依据应用Larson-Miller参数法计算了危险段炉管的剩余寿命,为炉管寿命监测系统应力集中、预测危险区域提供依据。     

铅酸电池剩余放电时间的研究

针对铅酸电池的电压与剩余放电时间之间的关系,建立了指数函数模型来模拟整个放电过程。为尽量降低MRE,该方法应用大量实验室数据选择恰当的模型做数据拟合的过程。首先,根据MRE的定义选择恰当的数据,利用MATLAB软件给出电压与剩余放电时间之间的指数模型;其次,找出电压与剩余放电时间模型的系数与电流之间的函数关系,进而得到电压与剩余放电时间和电流之间的函数模型;最后,用逐步迭代法建立电压与剩余放电时间和衰减状态之间的函数模型。通过对模型精确度的评估证明用指数模型来模拟放电过程是合理的,MRE都控制在2%之内。     

基于SPM的多变量连续过程在线故障预测方法

研究了一类模型未知带有隐含故障的多变量连续过程故障预测问题。基于统计过程监测(SPM)方法,提出了一种上述故障预测问题的解决方案。该方案首先利用正常状态下的样本数据建立主成分分析(PCA)模型,然后根据该模型构造出预测特征量,最后对该特征量进行时间序列分析和预测,从而预测出系统的剩余有效寿命(RUL)。针对线性时不变系统构造了预测特征量,并分析了在一定的系统结构假设和故障假设下的剩余有效寿命预测误差。基于CSTR的仿真实例说明了该方法的有效性。     

河道砂体地质建模技术在A油田的应用

A油田1076砂体主要储层为明化镇组曲流河沉积。依据储层预测成果精细雕刻河道砂体,井震联合建立构造模型;求取岩相与储层预测波阻抗之间的对应关系建立岩相分布概率,采用序贯指示模拟建立岩相模型;然后在岩相控制下,以波阻抗体作为同位协同克里金约束条件,同时去除河道砂体的垂向韵律趋势对变差函数分析的影响,采用序贯高斯方法模拟属性模型。后经过实际钻井数据及预留井验证,降低了随机建模的不确定性,提高了模型物性预测的精度,也更符合储层特征。     

基于改进回声状态网络的游离氧化钙预测控制

在非线性时延水泥烧成系统中,针对传统预测控制方法调节时间长、控制精度不高的问题,提出一种改进的在线型回声状态网络预测控制模型。首先将带有L1范数约束项的递归最小二乘法与回声状态网络相结合构建在线型预测模型,解决传统预测控制模型辨识精度较低、无法进行实时预测的问题;然后基于改进的回声状态网络预测模型,构建预测控制模型结构,并采用具有全局优化能力的粒子群算法进行滚动优化,保证实际输出量快速、准确、平稳地跟随被控量的设定值;最后利用改进的预测控制模型对水泥烧成系统中的游离氧化钙含量进行预测控制仿真实验,结果表明改进的预测控制模型具有良好的性能和应用前景。     

基于鲸鱼算法优化深度极限学习机的锂离子电池剩余使用寿命间接预测

鉴于对锂离子电池直接预测剩余使用寿命（RUL）困难，而极限学习机预测效果不稳定的现状，提出基于等压降放电时间和深度极限学习机（DELM）相结合的间接预测方法。首先，在恒流放电过程中提取出表征电池性能退化的等压降放电时间，分析它与容量间的相关程度并选之作为间接健康因子；其次，引入鲸鱼优化算法（WOA）优化深度极限学习机模型参数，构建锂离子电池RUL预测模型。用锂离子电池数据集中的B0005、B0007两个电池进行实验，结果表明：基于等压降放电时间的WOA-DELM模型预测方法相较于BP神经网络、DELM和PSO-DELM，能够更加准确地预测出锂离子电池的RUL，预测误差±5%，具有较好的预测精度和较快的收敛速度。     

基于时间序列ARMA模型的拱桥施工变形预测

为了促进时间序列分析方法在桥梁施工监测中的应用,利用时间序列ARMA模型对某特大桥主桥施工监控过程中主拱肋控制点变形数据进行分析,预测了后续主拱肋施工阶段的变形情况,并与实测数据进行比较。结果表明,时间序列ARMA模型在桥梁施工中预测拱肋变形具有较高的精度和可靠性,为桥梁施工的控制和监测提供了有效的手段。该研究成果说明时间序列分析方法可大大地改善参数的估计精度,提高模型的预测效果。     

粒子群优化神经网络的电镀金刚石套钻使用寿命预测

电镀金刚石套钻广泛应用各种加工领域,而套钻使用寿命受到多种因素影响,具有一定的非线性变化特点,为了准确预测电镀金刚石套钻的使用寿命,提出了基于粒子群优化神经网络的电镀金刚石套钻使用寿命预测模型。对电镀金刚石套钻使用寿命预测现状进行分析,针对BP神经网络参数优化问题,采用粒子群优化算法确定最优参数,建立电镀金刚石套钻使用寿命的预测模型,通过仿真实验对其有效性和优越性进行分析。实验结果表明,模型可以准确刻画影响参数与电镀金刚石使用寿命之间的变化关系,获得比对比模型更高的预测精度,实际应用价值更高。     

基于改进回声状态网络的游离氧化钙预测控制

在非线性时延水泥烧成系统中,针对传统预测控制方法调节时间长、控制精度不高的问题,提出一种改进的在线型回声状态网络预测控制模型。首先将带有L1范数约束项的递归最小二乘法与回声状态网络相结合构建在线型预测模型,解决传统预测控制模型辨识精度较低、无法进行实时预测的问题;然后基于改进的回声状态网络预测模型,构建预测控制模型结构,并采用具有全局优化能力的粒子群算法进行滚动优化,保证实际输出量快速、准确、平稳地跟随被控量的设定值;最后利用改进的预测控制模型对水泥烧成系统中的游离氧化钙含量进行预测控制仿真实验,结果表明改进的预测控制模型具有良好的性能和应用前景。     

某输气管道基于内检测的腐蚀评价与维修决策

对某输气管道内检测数据中金属损失缺陷进行统计分析,并结合缺陷剩余强度评价和未来状况预测,确定缺陷维修响应计划,提出管道下一次检测时间建议。评价结果表明,该管道当前完整性状况良好,所有缺陷在管道当前运行工况下均处于安全状态,建议关注3处计划响应时间在8年内的内腐蚀缺陷,并在2022年再次开展内检测。同时,建议管道企业维修响应计划的制定应基于缺陷深度和强度。     

基于粗糙集理论的决策树构造算法

应用粗糙集理论,提出了一种利用新的启发式函数构造决策树的方法。该方法以属性重要性评价指标作为信息熵函数,对条件属性进行选择,充分考虑了属性间的依赖性和冗余性,弥补了ID3算法对属性间依赖性强调不够的缺点,解决了决策树中子树的重复和有些属性在同一决策树上被多次选择的问题,该方法还能对不相容决策表进行正确分类。实例表明该方法是正确有效的,而且明显优于传统的决策树构造方法。     

基于决策树的三组元精馏序列结构最优合成规则识别

针对三组元精馏系统结构的优化合成,提出一种数据驱动的基于信息熵最小化的分类回归决策树（CART）模型。三组元精馏优化数据采用文献中严格模拟优化的结果,数据包含4种三组元混合物、34种进料组成以及7个候选精馏序列结构的最优化设计结果,生成数据集用来训练CART决策树。由决策树训练结果给出了三组元精馏结构最优设计决策规则,模型测试结果显示本文提出的决策树模型对数据集范围内三组元物系精馏结构决策的准确率为88.2%,同时表明了影响三组元最优精馏序列的主要影响因素及其重要性。     

Bayesian sequential joint detection and estimation

Abstract

Joint detection and estimation refers to deciding between two or more hypotheses and, depending on the test outcome, simultaneously estimating the unknown parameters of the underlying distribution. This problem is investigated in a sequential framework under mild assumptions on the underlying random process. We formulate an unconstrained sequential decision problem, whose cost function is the weighted sum of the expected run-length and the detection/estimation errors. Then, a strong connection between the derivatives of the cost function with respect to the weights, which can be interpreted as Lagrange multipliers, and the detection/estimation errors of the underlying scheme is shown. This property is used to characterize the solution of a closely related sequential decision problem, whose objective function is the expected run-length under constraints on the average detection/estimation errors. We show that the solution of the constrained problem coincides with the solution of the unconstrained problem with suitably chosen weights. These weights are characterized as the solution of a linear program, which can be solved using efficient off-the-shelf solvers. The theoretical results are illustrated with two example problems, for which optimal sequential schemes are designed numerically and whose performance is validated via Monte Carlo simulations.     

A sequential sampling plan for exponential distribution

In this article, a sequential variable sampling plan is studied. Suppose that the quality of an item in a batch is measured by a random variable with exponential distribution; its parameter is unknown having a gamma prior distribution. Then by using Bayesian approach and considering a Markov decision process, the optimality equations for the minimum total expected cost are formulated. We show that an optimal decision rule will have a control limit structure and monotonicity. A backward induction method is suggested that is a finite algorithm for the numerical solution of the sequential sampling plan.     

Discussion on “Second-Guessing Clinical Trial Designs” by Jonathan J. Shuster and Myron N. Chang

Abstract

Redesigning previously conducted clinical trials is a useful tool for better determining the impact of an alternative design. Shuster and Chang suggest the redesign of clinical trials that do not use sequential monitoring by imposing a sequential monitoring structure and determining what would have happened had such a structure been employed. However, early stopping decisions are complex and involve are intimate understanding of ethical, logistical, and statistical issues. “Second-guessing” a data and safety monitoring board is dangerous without this intimate understanding.     

Truncated SPRTs with application to multivariate normal data

We develop truncated sequential probability ratio test (SPRT) procedures for multivariate normal data. The framework includes a general cost structure and arbitrary mean and covariance structures. The truncated SPRT solutions have a practical and easy-to-use decision boundary representation. In the homogeneous case, a very fast recursive algorithm is presented for calculating the decision boundaries. Misclassification rates and expected sample size are investigated and the results are compared with a nonsequential procedure. A real-life data set on kidney dysfunction following heart surgery is used to illustrate the truncated SPRT procedure.     

Sequential estimation with data-dependent allocation and time trends

This note concerns the estimation of treatment difference following a sequential test in which two treatments are to be compared and treatment allocation is data-dependent. Woodroofe(1989) considered this problem when the responses are independent and identically distributed. In this paper, it is shown that woodroof'es asymptotic results also work well for the modified sequential test of coad (1991), which allows for possible linear time trends in the data.     

Ecommerce interface colour and consumer decision making: Two routes of influence

This article reports an empirical study of the effects of interface colour (blue vs. grey) on ecommerce decision making. Participants viewed a set of products and information on the attributes of each and then made a series of purchase decisions that provided the basis for individual rankings of this set. Results support two proposed ‘routes of influence’. In the first, interface colour influences the cognitive capacities and strategies of consumers. This was evident as participants considered more attributes in the grey interface condition. Importantly, this was not mediated by participants' affective state. In the second, interface colour exerts influence via participants' aesthetic judgements. This was evident at a product‐specific level—with colour‐related differences in product selection decisions mediated (for two product alternatives) by participants' assessments of product aesthetics. There was also some support for a product‐generic effect of interface colour—with product aesthetics tending to be more influential in the grey condition. Overall, the results demonstrate the multifacetted nature of the influence of interface colour on consumer decision making in retail environments. © 2011 Wiley Periodicals, Inc. Col Res Appl, 2011;