VMS诱导信息影响下的路径选择行为分析

正确理解可变情报板(VMS)诱导信息影响下的驾驶员路径选择行为,是高效发挥VMS作用的必然要求.采用SP调查(意向调查)探索VMS同时提供快速路和替换路径行程时间条件下的路径选择行为,采用离散选择分析方法对影响路径选择的因素进行了多变量分析,建立了描述路径选择概率的二元probit模型.Probit模型中的行程时间节省量这一解释变量的系数视为服从对数正态分布的随机系数,以反映行程时间重要性在人群中的不纯一性(heterogeneity).分析表明,驾驶员的路径选择会受VMS诱导信息显著影响,VMS影响大小取决于VMS信息内容、驾驶员个体属性(年龄、驾龄、用车类型以及快速路使用频率)、以及替换路径属性(所含信控交叉口数目).具体地,(a)VMS所告知的行程时间节省量越大.改道可能性越大;(b)年轻和年长者较之中等年龄者,改道可能性更大;驾龄越长,改道可能性越大;非单位公车驾驶员改道可能性更大;使用快速路频率越低,改道可能性越大,(c)替换路径所含信控交叉口越多,改道可能性越小.研究成果可为更好地设计、运行和评价VMS信息发布策略提供参考.     

资本市场多标度离散随机分割级串模型

在收益率波动层次结构理论上构建了一种新的波动级串结构模型,通过对基元分割概率中两个关键控制参数不同设定的Monte-Carlo仿真分析发现,分割数取随机整数能够显著地改善模型的拟合优度,自相关函数也表现出类似经验数据衰减的动力学特征,随机控制变量选取normal、log-normal、possion和t分布不能进一步改善基于均匀分布级串模型的拟合效果.此外,选取的最优波动级串模型还能够很好地复制出2<α<4的负幂律衰减和多重分形特征,表明该级串模型能够作为经验数据的可靠拟合模型.     

多处理机系统上并行程序的串行仿真

本文给出多处理机系统上并行程序计算过程的一般描述。引进元事件的概念,将并行计算过程归化成一个离散事件系统的动态过程。文中给出该过程在串行计算机上的仿真原理和在具MC68000系列微处理器的计算机系统上的实现方法。     

基于JPEG国际标准的图像压缩方法的研究

本文介绍了静态图像国际标准编码ＪＰＥＧ算法，对ＪＰＥＧ算法的三种类型的编码方法进行了分析和探讨，提出了一种新的快速ＤＣＴ算法，编制了基本型编码的ＪＰＥＧ算法软件，经实验验证，取得了满意的效果。     

一类非线性抛物型方程的线性化差分格式

用离散能量法证明Forsythe和Wasow著作中提出的一类非线性抛物型方程线性化差分格式的收敛性与稳定性。     

离散数学与高中数学新课标中常用逻辑用语的衔接研究

作者在教材分析的基础上，通过对高中数学新课程标准中命题及其关系、简单的逻辑联结词、充分条件、必要条件、全称量词、存在量词与离散数学中的命题符号化及联结词、推理理论、一阶逻辑知识的比较，研究其异同点，从而更好地指导大学离散数学的教学。     

LBE–DEM simulation of inter-phase heat transfer in gas–solid cross jets

Lattice-Boltzmann equation(LBE)–Discrete element method(DEM)coupled simulation of a twodimensional gas–solid cross jet is performed,focusing on the gas-particle two-way coupling effect on heat transfer characteristics.The Reynolds number is 1000,and particle Stokes numbers are 10,25,and 50 under the same number flow rate of particles.The gas phase temperature field and particle distribution as well as the inter-phase heat transfer characteristics are studied and analyzed.The dominating effects,i.e.the mean temperature difference and mean heat transfer coefficient between the gas–solid phases,for the pre-and post-collision stages of the cross jets are illustrated respectively.The change of dominating roles is related to the dynamical response characteristics of particles.     

The representation of three-way proximity data by single and multiple tree structure models

Models for the representation of proximity data (similarities/dissimilarities) can be categorized into one of three groups of models: continuous spatial models, discrete nonspatial models, and hybrid models (which combine aspects of both spatial and discrete models). Multidimensional scaling models and associated methods, used for thespatial representation of such proximity data, have been devised to accommodate two, three, and higher-way arrays. At least one model/method for overlapping (but generally non-hierarchical) clustering called INDCLUS (Carroll and Arabie 1983) has been devised for the case of three-way arrays of proximity data. Tree-fitting methods, used for thediscrete network representation of such proximity data, have only thus far been devised to handle two-way arrays. This paper develops a new methodology called INDTREES (for INdividual Differences in TREE Structures) for fitting various(discrete) tree structures to three-way proximity data. This individual differences generalization is one in which different individuals, for example, are assumed to base their judgments on the same family of trees, but are allowed to have different node heights and/or branch lengths.We initially present an introductory overview focussing on existing two-way models. The INDTREES model and algorithm are then described in detail. Monte Carlo results for the INDTREES fitting of four different three-way data sets are presented. In the application, a single ultrametric tree is fitted to three-way proximity data derived from intention-to-buy-data for various brands of over-the-counter pain relievers for relieving three common types of maladies. Finally, we briefly describe how the INDTREES procedure can be extended to accommodate hybrid modelling, as well as to handle other types of applications.     

离散广义大系统的渐近稳定与镇定

广义大系统的渐近稳定与镇定问题是广义大系统理论的基本问题之一 ,在许多领域均有广泛的应用。广义大系统的研究与广义系统相比困难得多。利用广义Lyapunov函数方法研究了离散广义大系统的渐近稳定与镇定问题 ,给出了渐近稳定的判定定理 ,设计了适当的反馈律 ,以实现离散广义大系统的镇定。该方法简单、直观 ,给出的例子说明了该定理的可行性。     

广义范数残差判据

本文讨论了利用正交变换方法的最小二乘递推算法,提出了广义范数残差的概念,建立了相应的广义范数残差判据,用来离线或在线评价参数和模型结构估计的可靠程度。仿真结果证实了这种判据在解决系统辨识问题时的可行性。