Data Assimilation Method Based on the Constraints of Confidence Region

The ensemble Kalman filter(En KF) is a distinguished data assimilation method that is widely used and studied in various fields including methodology and oceanography. However, due to the limited sample size or imprecise dynamics model, it is usually easy for the forecast error variance to be underestimated, which further leads to the phenomenon of filter divergence.Additionally, the assimilation results of the initial stage are poor if the initial condition settings differ greatly from the true initial state. To address these problems, the variance inflation procedure is usually adopted. In this paper, we propose a new method based on the constraints of a confidence region constructed by the observations, called En CR, to estimate the inflation parameter of the forecast error variance of the En KF method. In the new method, the state estimate is more robust to both the inaccurate forecast models and initial condition settings. The new method is compared with other adaptive data assimilation methods in the Lorenz-63 and Lorenz-96 models under various model parameter settings. The simulation results show that the new method performs better than the competing methods.     

渤海和南海海域极值风速的置信区间

目前我国海洋台站积累的实测日最大风速资料长度还较短，本文提出采用实测日4次（或3次）平均风速产生日最大风速样本的方法。认为极值风速是随机变量，采用本文方法产生的日最大风速样本，统计推算了渤海和南海海域15个台站的若干年一遇极值风速的统计参数，得到了不同重现期的不同置信水平的极值风速区间，为更合理地确定海洋平台结构设计风荷载提供了依据。     

Estimation of background levels of contaminants

Samples from hazardous waste site investigations frequently come from two or more statistical populations. Assessment of background levels of contaminants can be a significant problem. This problem is being investigated at the U.S. Environmental Protection Agency's Environmental Monitoring Systems Laboratory in Las Vegas. This paper describes a statistical approach for assessing background levels from a dataset. The elevated values that may be associated with a plume or contaminated area of the site are separated from lower values that are assumed to represent background levels. It would be desirable to separate the two populations either spatially by Kriging the data or chronologically by a time series analysis, provided an adequate number of samples were properly collected in space and/or time. Unfortunately, quite often the data are too few in number or too improperly designed to support either spatial or time series analysis. Regulations typically call for nothing more than the mean and standard deviation of the background distribution. This paper provides a robust probabilistic approach for gaining this information from poorly collected data that are not suitable for above-mentioned alternative approaches. We assume that the site has some areas unaffected by the industrial activity, and that a subset of the given sample is from this clean part of the site. We can think of this multivariate data set as coming from two or more populations: the background population, and the contaminated populations (with varying degrees of contamination). Using robust M-estimators, we develop a procedure to classify the sample into component populations. We derive robust simultaneous confidence ellipsoids to establish background contamination levels. Some simulated as well as real examples from Superfund site investigations are included to illustrate these procedures. The method presented here is quite general and is suitable for many geological and biological applications.     

基于地下水动力特征监测的岩溶塌陷预警阈值探索——以广州金沙洲岩溶塌陷为例

监测预警是岩溶塌陷地质灾害防治领域急需解决的技术难题。文章在总结当前岩溶塌陷监测预警研究现状的基础上,以广州金沙洲地区岩溶塌陷监测为例,通过对不同岩溶塌陷阶段地下水动力条件监测数据分析,发现数据异常值反映了不同工况地下水动态和岩溶塌陷发展阶段的突变关系,以此为基础,通过曲线拟合和残差分析确定了岩溶塌陷预警的置信带。通过对比分析异常值出现最多次数时间,最大及最小异常值出现时间和实际岩溶塌陷发生时间,验证了运用异常数据分析法进行岩溶塌陷预警是可行的,监测数据间隔越密,捕获的异常值越多,预警越准确。      

空间数据挖掘中关联规则的支持度和可信度研究

空间数据挖掘中所依赖的空间相关性是由空间关联规则描述的.研究了事务集为粗糙集时空间关联规则支持度和可信度的计算方法;提出了当事务集为粗糙集、空间数据为模糊数据时的模糊粗糙关联规则.同时,推导了空间关联规则的支持度和可信度的变化规律.     

流量Ⅲ型误差的分析

以表达流量精确度的综合标准差公式为依据,用置信水平85%与综合计算提高了误差指标值的安全程度和准确程度,应用15个测站296次流量Ⅲ型误差试验资料分析确定了单站计算法与综合计算法两套流量Ⅲ型误差实用方案,有效地控制了流量误差并提高了流量精度,且综合计算法优于单站计算法。分析研究成果明显改进了河流流量测验规范的相关规定,为其修订提供了重要依据。     

Evaluation of confidence intervals for a steady-state leaky aquifer model

The fact that dependent variables of groundwater models are generally nonlinear functions of model parameters is shown to be a potentially significant factor in calculating accurate confidence intervals for both model parameters and functions of the parameters, such as the values of dependent variables calculated by the model. The Lagrangian method of Vecchia and Cooley [Vecchia, A.V. & Cooley, R.L., Water Resources Research, 1987, 23(7), 1237–1250] was used to calculate nonlinear Scheffé-type confidence intervals for the parameters and the simulated heads of a steady-state groundwater flow model covering 450 km² of a leaky aquifer. The nonlinear confidence intervals are compared to corresponding linear intervals. As suggested by the significant nonlinearity of the regression model, linear confidence intervals are often not accurate. The commonly made assumption that widths of linear confidence intervals always underestimate the actual (nonlinear) widths was not correct. Results show that nonlinear effects can cause the nonlinear intervals to be asymmetric and either larger or smaller than the linear approximations. Prior information on transmissivities helps reduce the size of the confidence intervals, with the most notable effects occurring for the parameters on which there is prior information and for head values in parameter zones for which there is prior information on the parameters.     

Displacement limits and performance displacement profiles in support of direct displacement‐based seismic assessment of bridges

Displacement limits and performance displacement profiles (PDPs) for the direct displacement‐based assessment of existing bridges are proposed. The PDPs are defined as the bridge inelastic deformed shapes associated with the attainment of selected damage states in some critical elements of the bridge. In the paper, displacement limits are provided for piers, abutments, joints, bearing devices and shear keys. Moreover, different approaches for the definition of the PDP are examined, including adaptive pushover analysis, effective modal analysis, and rational analysis of simplified bridge models. In the paper, the key aspects and modeling assumptions of the proposed direct displacement‐based assessment procedure are presented first. This is followed by some examples of application to typical Italian highway bridge configurations, differing in pier layout, deck type, and pier‐deck connections. Copyright © 2013 John Wiley & Sons, Ltd.