Recursive partition and amalgamation with the exponential family: Theory and applications

The theory of tree-growing (RECPAM approach) is developed for outcome variables which are distributed as the canonical exponential family. The general RECPAM approach (consisting of three steps: recursive partition, pruning and amalgamation), is reviewed. This is seen as constructing a partition with maximal information content about a parameter to be predicted, followed by simplification by the elimination of ‘negligible’ information. The measure of information is defined for an exponential family outcome as a deviance difference, and appropriate modifications of pruning and amalgamation rules are discussed. It is further shown how the proposed approach makes it possible to develop tree-growing for situations usually treated by generalized linear models (GLIM). In particular, Poisson and logistic regression can be tree-structured. Moreover, censored survival data can be treated, as in GLIM, by observing a formal equivalence of the likelihood under random censoring and an appropriate Poisson model. Three examples are given of application to Poisson, binary and censored survival data.     

Numerical solutions of the shallow water equations with discontinuous bed topography

A simple scheme is developed for treatment of vertical bed topography in shallow water flows. The effect of the vertical step on flows is modelled with the shallow water equations including local energy loss terms. The bed elevation is denoted with z_b^‐ for the left and z_b⁺ for the right values at each grid point, hence exactly representing a discontinuity in the bed topography. The surface gradient method (SGM) is generalized to reconstruct water depths at cell interfaces involving a vertical step so that the fluxes at the cell interfaces can accurately be calculated with a Riemann solver. The scheme is verified by predicting a surge crossing a step, a tidal flow over a step and dam‐break flows on wet/dry beds. The results have shown good agreements compared with analytical solutions and available experimental data. The scheme is efficient, robust, and may be used for practical flow calculations. Copyright © 2002 John Wiley & Sons, Ltd.     

模糊对向传播网络数据融合目标识别方法

重点研究了模糊对向传播网络 (FCPN)模型。针对数据融合和目标识别的特点 ,提出了基于模糊对向传播网络的融合目标识别方法和改进的模糊对向传播网络 (MFCPN)融合结构。利用仿真数据对网络的训练算法和融合结构进行了实验研究。结果表明 ,模糊对向传播网络较误差后向传播网络 (BPN)能够有效地实现融合识别 ;改进的模糊对向传播网络融合结构是可行的。同时还对FCPN和MFCPN应用于前视红外 (FLIR)和可见光摄像机目标跟踪系统进行了应用研究。     

用AD590自组数字温度计的设计实验

本介绍了用ADS90自组数字温度计实验，说明了实验步骤和数据处理等过程。     

六台轧机热轧钢板在线测长及产品统计微机系统

本论文选用Apple-Ⅱ作主机,开发了一套外设接口扩展箱和相应的应用软件,用于实现在钢厂中对六台单轧机的热轧钢板长度在线检测和现场显示,同时对钢板的长度按照合格、超长、超短进行分类统计,打印生产报表。此外还提供随时修改钢板长度(标尺)设定值和随机查询各台轧机产质量状况的功能。在接口扩展箱中,采用了包括光电耦合在内的若干抗干扰措施,保证系统能在钢厂恶劣环境中正常运行。本系统已在工厂轧机上试用成功。     

Estimation of integrated volatility in stochastic volatility models

In the framework of stochastic volatility models we examine estimators for the integrated volatility based on the pth power variation (i.e. the sum of pth absolute powers of the log‐returns). We derive consistency and distributional results for the estimators given high‐frequency data, especially taking into account what kind of process we may add to our model without affecting the estimate of the integrated volatility. This may on the one hand be interpreted as a possible flexibility in modelling, for example adding jumps or even leaving the framework of semimartingales by adding a fractional Brownian motion, or on the other hand as robustness against model misspecification. We will discuss possible choices of p under different model assumptions and irregularly spaced data. Copyright © 2005 John Wiley & Sons, Ltd.     

The Iyengar Type Inequalities with Exact Estimations and the Chebyshev Central Algorithms of Integrals

In this paper, both low order and high order extensions of the Iyengar type inequality are obtained. Such extensions are the best possible in the same sense as that of the Iyengar inequality. hzrthermore, the Chebyshev central algorithms of integrals for some function classes and some related problems are also considered and investigated.     

云南数字台网谱震级的测定和地震辐射能的计算

运用Duda等提出的谱震级测定公式,结合云南区域数字台网宽频带记录资料测定了发生在网内的中强震(4.0相似文献   

非等间距序列建模过程中存在的问题及改进

在研究非等间距序列的基础上 ,本文将非等间距累加运用于非等间距序列的建模过程中 ,使原有模型得到改进 .实例表明 ,改进后模型的精度有了很大提高     

基于多元时间序列融合的飞行动作识别方法

针对飞行动作数据随机性强与长度不一致的问题,提出通过减小动态时间规整(DTW)算法的搜索空间,并定义不同特征参数贡献度的概念,实现对飞行数据的多元时间序列融合,从而完成对战术机动动作的识别。通过引入预分类和细分类结合的方式,对动作数据进行预处理,然后根据改进的动态时间规整(WDTW)算法对待测数据进行识别。仿真实验表明,相比传统DTW算法,WDTW算法通过降低算法复杂度,识别计算时间变化明显;对核密度与精准度系数的分析表明识别准确率亦有所提高。实验结果验证了所提方法的准确性。