Random binary matrices in biogeographical ecology—Instituting a good neighbor policy

Binary matrices originating from presence/absence data on species (rows) distributed over sites (columns) have been a subject of much controversy in ecological biogeography. Under the null hypothesis that every matrix is equally likely, the distributions of some test statistics measuring co-occurrences between species are sought, conditional on the row and column totals being fixed at the values observed for some particular matrix. Many ad hoc methods have been proposed in the literature, but at least some of them do not provide uniform random samples of matrices. In particular, some swap algorithms have not accounted for the number of neighbors each matrix has in the universe of matrices with a set of fixed row and column sums. We provide a Monte-Carlo method using random walks on graphs that gives correct estimates for the distributions of statistics. We exemplify its use with one statistic.     

On the random placement hypothesis

A traditional method of summarizing spatial distribution of species is the observed species-area curve. Often the observed species-area curve is surprisingly close to the expected species-area curve under the hypothesis of random placement of individuals. This has been used as evidence supporting the hypothesis. In this paper, we argue that using the observed species-area curve to test the general random placement hypothesis is highly inefficient. We present a testing method based on the classical ² test for over-dispersion which is not only more efficient but also applicable to situations where complete abundance information are unavailable. We also discuss three alternatives of the hypothesis. The focus of this paper is on these and other general issues relevant to communities of different types. No applications are included in this paper.     

Comparison of Spatial Methods for the Assessment of Planktonic Patches

Planktonic patches are defined as areas where the abundance of plankters is above a threshold value τ. The estimation of patch size and shape can be approached using spatial statistical tools, using truncated random fields or indicator random fields as classifiers. In all cases there is the risk of false positive and false negative errors. In this paper we present the results of a comparative study on the performance of four commonly used methods: conditional simulation and kriging, both in the original measurement units of the data and under an indicator transform. We used a misclassification cost function to compare the four methods. Our results show that conditional simulation in the original measurement units attains the lowest misclassification cost. We also illustrate how the point at which this minimum is attained can be used to chose an optimal cut-off value for binary classification. Received: December 2003 / Revised: June 2005     

疲劳损伤等效在随机振动试验中的应用

以疲劳损伤等价为基础的随机振动试验是评价结构振动环境适应性能力的重要手段.将基于位移模态和应变模态的模态叠加方法分别应用于结构振动位移响应和应力响应的分析中,建立了随机振动试验不同激励条件下,结构振动响应的关系;将结构随机振动应力响应的峰值概率分布通用关系应用于疲劳损伤评估,导出了振动疲劳损伤等效关系.以一个试验为例介绍了疲劳损伤等效原则在随机振动试验中的应用.     

明渠中有机质微粒沉降过程的随机游走模拟

基于明渠流动的主要特点,考虑紊动强度的垂向非均匀性,及颗粒运动的游荡效应（loitering effect）影响,对微粒运动基本方程进行改进,建立了明渠非均匀紊流中考虑游荡效应的随机游走模型,对明渠中微粒的沉降损失进行了模拟分析.模拟结果显示,不考虑游荡效应影响时,明渠中微粒的沉降损失率可用微粒沉速与水深之比计算;而在游荡效应影响下,微粒沉降损失率会发生约18%~27%的下降,下降百分比与均匀紊流中微粒沉速在游荡效应影响下的折减百分比渐近值（19~25%）基本一致.本文结论基于不考虑微粒重悬浮、游荡效应为紊流对微粒沉降的主导影响机理等前提,主要适用于对明渠中细小有机质微粒沉降至床底过程更准确的计算分析.     

基于机器学习的恐怖袭击事件后果预测方法研究

恐怖袭击事件通常会造成严重的人员伤亡、财产损失和社会影响，针对在不同场景下发生恐怖袭击所造成的后果进行预测是目前应对恐怖袭击事件急需解决的问题之一。利用多源数据，首先基于随机森林算法对恐怖袭击事件是否造成死伤进行分类预测，进而基于岭回归算法预测事件造成的具体死伤人数。研究结果表明:随机森林在测试集上对有死伤事件的召回率达到0.85，岭回归预测死亡和受伤人数的平均绝对误差分别小于1人和2人。研究结果可为反恐资源配置优化、预防恐怖袭击事件和减少其造成的损害提供辅助决策支持。     

基于纠错码的指纹加密算法研究

对指纹加密算法进行整体介绍,并加入纠错机制,设计了带纠错功能的指纹加密算法。该法利用二进制序列发生器生成随机以多项式的系数形式的密钥,将指纹点加密,在密钥恢复阶段用拉格朗日差值来恢复多项式,并利用循环冗余校验码进行校验,可以保证找到最准确的密钥来保证多项式的准确度。实验结果表明:利用带有纠错码的模糊金库算法很好地实现了指纹模板的加密和解密,从而达到了保护生物信息安全的要求;通过密钥长度增长可以提高系统的安全性能。     

对随机振动试验方法的探讨

本文详细介绍了随机振动试验过程中存在的振台推力估算方法、夹具设计安装、控制/响应传感器的安装方法,对试验前的准备及试验过程的实施进行了描述,探讨了试验过程中发生的中断及其处理方法。     

基于可能-概率测度转换的危险品运输风险分析

为解决不确定环境下的风险分析问题,针对危险货物运输中风险参数具有不确定性、随机性和模糊性的特点,建立基于概率测度-可能性测度转换原则和模糊逻辑的危险货物运输风险分析方法。首先对具有模糊性的参数直接建立模糊数,对具有随机性的参数建立随机数;接着依据概率测度向可能性测度转换的最优原则,将随机数转换为模糊数;然后根据模糊运算法则进行风险计算和分析。最后通过一个算例验证了模型和算法的有效性。结果表明,提出的方法能处理随机和模糊环境下的风险分析问题,能为风险分析尽可能多地保留不确定性信息,尽可能少地丢失有用信息。     

沿海和河口城市防灾设防标准系统分析

本文针对天津、上海、青岛等三种不同类型的沿海、河口城市，运用灰色理论、随机模拟等方法进行了洪水、风暴湖、巨浪等环境因素的计算，并进行了灾害经济损失的风险分析，给出了不同的防灾设防标准。