抗野值自适应卡尔曼滤波方法的研究

针对陀螺漂移信号中野值的不良影响。从量测噪声自适应Kalman滤波算法出发，首次提出了抗野值自适应Kalman滤波方法，并在其基础上进行了分析，提出一种改进的算法．通过对某型号高精度寻北仪中的试验证明，该算法能够有效去除寻北仪信号中的野值，提高寻北仪的寻北精度，并且对系统的量测噪声不敏感．     

ATM交易状态特征分析与异常检测

考虑ATM交易过程当中产生的一系列参数,如交易量、交易成功率和响应时间等,对交易状态特征进行分析并建立了异常检测模型。针对成功率与响应时间2个参数,利用聚类算法将数据点划分为正常点、疑似异常点、异常点3大类。对于疑似的异常点,再根据其时间序列周围点的分布情况确定是否确实为异常点;对于交易量参数,首先通过LOF局部离群因子对离群点进行识别,再结合交易量随时间的移动均线及标准差加以辅助筛选,得到初步的疑似异常点,进一步通过与不同天同一时刻数据进行比较,最终确定是否为异常点。根据上述模型,本文将异常情况划分为3个预警等级,并对重大故障情况进行预测。     

Detection of material property errors in handbooks and databases using artificial neural networks with hidden correlations

The authors have discovered a systematic, intelligent and potentially automatic method to detect errors in handbooks and stop their transmission using unrecognised relationships between materials properties. The scientific community relies on the veracity of scientific data in handbooks and databases, some of which have a long pedigree covering several decades. Although various outlier-detection procedures are employed to detect and, where appropriate, remove contaminated data, errors, which had not been discovered by established methods, were easily detected by our artificial neural network in tables of properties of the elements. We started using neural networks to discover unrecognised relationships between materials properties and quickly found that they were very good at finding inconsistencies in groups of data. They reveal variations from 10 to 900% in tables of property data for the elements and point out those that are most probably correct. Compared with the statistical method adopted by Ashby and co-workers [Proc. R. Soc. Lond. Ser. A 454 (1998) p. 1301, 1323], this method locates more inconsistencies and could be embedded in database software for automatic self-checking. We anticipate that our suggestion will be a starting point to deal with this basic problem that affects researchers in every field. The authors believe it may eventually moderate the current expectation that data field error rates will persist at between 1 and 5%.     

High Breakdown Estimation for Multiple Populations with Applications to Discriminant Analysis

We consider S-estimators of multivariate location and common dispersion matrix in multiple populations. Instead of averaging the robust estimates of the individual covariance matrices, as used by Todorov, Neykov and Neytchev (1990), the observations are pooled for estimating the common covariance more efficiently. Two such proposals are evaluated by a breakdown point analysis and Monte Carlo simulations. Their applications to the discriminant analysis are also considered.     

单向分类随机效应模型的异常值检测

本文研究平衡的单向分类随机效应模型中单个异常值的检验问题,在随机效应的异常均值滑动模型下,导出异常值的检验统计量及其精确分析,并证明了该检验的一致最优无偏性,另外,对于误差变量的异常均值滑动模型,提出了一个近似的检验过程,并运用随机模拟给出该检验的临界值表,最后,对一组模拟数据进行说明。     

稳健算法及其在红外光谱分析中的应用

总结了稳健主成分分析、稳健主成分回归、稳健偏最小二乘回归和稳健连续回归等各种稳健算法的新近成果. 研究表明,稳健算法可以检测并规避异常值的影响. 稳健算法应用红外光谱分析中可望优化定性、定量预测模型.     

模糊卡尔曼滤波器在初始对准抗野值修正中应用

Kalman滤波器广泛应用于捷联导航系统，在实际系统中量测序列由于各种原因可能出现错误的量测值或野值，会影响滤波器的估计效果。采用基于模糊控制器的卡尔曼滤波器，可以有效减小野值对实际系统的影响，提高滤波质量，改善系统精度。     

异常交易行为的甄别研究

本文在无指导学习的研究框架下,运用分位数回归模型结合变点检验,对中国证券市场的异常交易行为进行甄别研究。通过分析持股比例变动与股价收益率间协同演化关系的异常,为甄别异常交易行为设立判别标准并客观的界定阈值提供了一种新的方法。基于这一方法监管者可以构建分期、分级、分类的实时监管体系,提高监管效率。     

温度影响下基于应力波的钛合金试件疲劳裂纹监测实验研究

本文对温度影响下应用应力波监测钛合金CT试件中的疲劳裂纹进行了研究。建立了由MTS材料试验机和温控箱组成的实验装置,模拟温度变化对应力波在钛合金试件中传播的影响。采用PZT压电元件分别在试件中激励和接收应力波信号。通过连续小波分析,提取应力波信号的多种特征用于表征疲劳裂纹的发生与发展,并对信号特征进行了统计分析。为在温度变化下监测钛合金试件中的疲劳裂纹,对信号特征进行多元偏值分析,采用马氏平方距离融合多个信号特征,在概率统计意义下确定钛合金试件中是否存在疲劳裂纹。实验结果表明了所提出方法的可行性和有效性。     

Robust partial least squares regression—part III,outlier analysis and application studies

This paper is the third part of the work on robust partial least squares (RPLS) regression. The paper focuses on implementation issues for outlier detection and diagnosis. Furthermore, the paper introduces a numerically more efficient algorithm for determining the Stahel–Donoho estimator (SDE). This has been identified as a potential drawback of the new proposed RPLS algorithm, detailed in Part II of this work. Finally, a total of three application studies are presented which involve data recorded from (i) a calibration experiment (similar number of variables/observations), (ii) a distillation process for purifying benzene (considerably more observations than variables) and (iii) an experiment of a multi‐component concentration determination using Raman spectroscopy (considerably more variables than observations). Copyright © 2008 John Wiley & Sons, Ltd.