稳健总体最小二乘Helmert方差分量估计

对于总体最小二乘而言,经常需要处理不同精度或者不同类型的观测数据,根据先验方差来定权往往不准确,同时观测数据中可能含有粗差。针对这两个问题,提出稳健总体最小二乘Helmert方差分量估计,将稳健估计和Helmert方差分量估计同时应用于总体最小二乘中。最后通过两个实验的计算结果表明,该方法是可行的、有效的。     

基于改进SVA的SAR/INSAR图像处理

针对现有的Spatially Variant Apodization (SVA)算法不能有效抑制旁瓣或损失主瓣能量的问题,本文提出了一种改进的SVA算法.该算法把传统的滤波器从3点扩展到5点,并且根据采样率的不同,设定相应的滤波器参数,得到满足约束优化理论的最优解.该算法适用于任意奈奎斯特采样率,既能有效地抑制旁瓣,又能保持主瓣的能量和信号的高分辨率;同时能够在一定程度上提高图像的信噪比,在干涉操作中增强复图像对的相关性.实验结果表明,与传统的频域加窗方法相比,该方法能够在保持图像高分辨率的前提下,更有效地抑制旁瓣;同时提高干涉操作的精度.     

Identification of coastal water quality by statistical analysis methods in Daya Bay, South China Sea

In this paper, cluster analysis (CA), principal component analysis (PCA) and the fuzzy logic approach were employed to evaluate the trophic status of water quality for 12 monitoring stations in Daya Bay in 2003. CA grouped the four seasons into four groups (winter, spring, summer and autumn) and the sampling sites into two groups (cluster DA: S1, S2, S4-S7, S9 and S12 and cluster DB: S3, S8, S10 and S11). PCA identified the temporal and spatial characteristics of trophic status in Daya Bay. Cluster DB, with higher concentrations of TP and DIN, is located in the western and northern parts of Daya Bay. Cluster DA, with the low Secchi, is located in the southern and eastern parts of Daya Bay. The fuzzy logic approach revealed more information about the temporal and spatial patterns of the trophic status of water quality. Chlorophyll a, TP and Secchi may be major factors for deteriorating water quality.     

Component correlations in structure‐specific seismic loss estimation

This paper addresses correlations between multiple components in structure‐specific seismic loss estimation. To date, the consideration of such correlations has been limited by methodological tractability, increased computational demand, and a paucity of data for their computation. The effect of component correlations, which arises in various forms, is however a significant factor affecting the results of structure‐specific seismic loss estimation and therefore it is prudent that adequate consideration be given to their effect. This paper provides the details of a tractable and computationally efficient seismic loss estimation methodology in which correlations can be considered. Methods to determine the necessary correlations are discussed, particularly those that can be used in the absence of sufficient empirical data, for which values are suggested based on the judgement. The effects of various assumptions regarding correlations are illustrated via application to a case‐study office structure. It is observed that certain correlation assumptions can lead to errors in excess of 50% in the lognormal standard deviation in the loss given intensity and loss hazard relationships, while full consideration of partial correlations is 50 times more computationally expensive than other assumptions. Copyright © 2009 John Wiley & Sons, Ltd.     

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虾类微量元素含量的主成分分析

应用主成分分析法对湛江几种养殖对虾和海捕天然对虾的微量元素的含量进行综合评价。结果表明:虾体中微量元素含量均衡;综合排名依次为野生斑节对虾、野生凡纳滨对虾、养殖斑节对虾、养殖凡纳滨对虾,两种野生对虾的综合排名均高于养殖对虾;野生斑节对虾综合得分为1.6708,微量元素含量最均衡,营养价值最高,养殖凡纳滨对虾营养价值最低,综合得分为-1.20943。     

求解大样本核主成分分析模型的Lanczos算法

求解核主成分分析模型的技术关键是确定核矩阵端部的较大特征对。把求解大规模对称矩阵端部特征对问题的基本方法--Lanczos算法应用于核主成分分析模型的求解,设计了大样本核主成分分析模型求解的实用算法。在clapack和nu TRLan两个软件包的基础上,开发了大样本核主成分分析模型求解算法的VC++程序。用高光谱遥感图像数据进行模型求解算法的应用试验研究,证明了大样本核主成分分析模型求解算法的实用性。     

主成分分析和熵值法相结合的水质综合评价模型及其在郑州市金水河的应用

水质评价对决策者决定水的使用功效尤为重要。水质综合评价系统中涉及到大量因子与指标,因子之间相互作用,致使水质的评价工作相对困难。主成分分析法可以消除因子间的相关性,因而被广泛应用于水质评价,但其忽略了数据离散程度的问题。熵值法则考虑了数据的离散特点。为更好地进行水质的综合评价,本文提出把主成分分析法和熵值法结合起来确定指标权重的方法,建立了水质评价模型,并采用该模型对郑州市金水河再生水2009年的水质情况进行评价,将评价结果与单独采用主成分分析或熵值法的结果进行了比较。结果表明了该方法的可行性与实用性,能够为非常规水资源利用提供理论依据和决策参考。     

综合国力主成分分析与模糊综合组合评价模型

基于模糊理论、统计分析等数学理论,提出一种定量的综合国力模糊综合评价模型.首先对基本数据进行标准化处理和主成分分析,并建立综合国力评判集;其次,根据所选取的主成分及其贡献值建立评判对象因素集,并计算综合国力评判因素权向量;最后,利用综合国力评判集、评判因素权向量及评判对象因素集进行模糊综合评判,根据模糊综合评判模型对13个主要国家的综合国力进行了比较分析.