板问题多重网格法收敛性的低模估计

１．引言 近年来,多重网格法已成为行之有效的偏微分方程数值解法．对板问题有限元离散系统的多重网格法,也有不少的研究工作,如［４］,［５］,［１０］,［１３－１７］．在［４］,［１４－１７］中,作者讨论了Ｃ１协调元离散板问题的多重网格法,并在能量模（即 Ｈ２模）意义下获得了最优的收敛率．在［５］,［１０］中,作者讨论了非协调元离散问题的多重网格法,并在能量模意义下获得了最优的收敛率,同时在能量模意义下证明了套迭代多重网格法一阶收敛．但对板问题多重网格法的低模估计,即 Ｈ１模估计,至今尚未见研究,本文…     

Wilson非协调元的V循环多重网格法 *

非协调有限元V循环多重网格法的收敛性至今仍是一个没有很好解决的问题 .给出了Wilson非协调有限元的两类V循环多重网格法的收敛性证明 .     

非对称不定问题的非协调多重网格法

１．引言设　是Ｒｄ（ｄ＝２;３）中的有界多角形区域,α是它的边界．考虑下列模型问题此处ｆ∈ＥＬ２（Ω）,系数ＡＥ（Ｃ１（Ω））ｄ×ｄ满足下列一致椭园条件此处α０是正常数．此外假设Ｂ∈（Ｃ１（Ω）ｄ和ｃ∈Ｃ０（Ω）（［１４］）．（１．１）式的变分形式是：找ｕ∈Ｈ０（Ω）使得最近,非对称不定问题的非协调多重网格法吸引了众多的研究,详见问,［７］;［１０］．考虑非协调元多重网格的一个重要原因是混合元和非协调元之间存在着紧密的联系（详见【几问,问）．设ＦＩ是ｆｉ拟一致的Ｈ角形或矩形剖分,是由连接Ｆ'－'（…     

一类非协调元的收敛性分析

１．引言最近,［１］在求解Ｓｔｏｋｅｓ方程时提出了一类非协调元．这类非协调元定义在矩形网格上,形式简单,自由度少,比熟知的多线性元还少．例如,对于三维问题,它们只有六个自由度,是型函数在各个表面中点处的函数值或者表面上的平均值．与一些熟知的非协调元不同之处是,由于这类非协调元简单的形式及其非常少的自由度,它们不包含任何协调的部分,但是,已有的结果表明它们具有良好的数值表现［１］,［２］中已有一些理论分析,用它们来求解晶体的微结构方程,也取得较好的结果．本文将详细分析这类非协调元的收敛性,所用的工…     

带补偿C^0非协调板元的多重网格法

本文考虑重调和方程的Ｃ０非协调元逼近．通过双线性型ｃｋ（ｕ，ｖ）引入的补偿和将多重网格法应用到Ｃ０非协调板元，给出了更精确的逼近．     

求解线性互补问题的乘性Schwarz算法的收敛速度估计

1．引言区域分解法是八十年代兴起并得到迅速发展及广泛应用的数值计算方法．和多重网格法一样，区域分解法用于求解椭圆边值问题时具有与剖分网格h无关的收敛速度［8］，因而是一种高效快速算法．八十年代末及九十年代初，这种区域分解思想也开始应用于障碍问题的求解［2－8，10。12，16］数值实验表明，该算法对于障碍问题也是有效的·但是，和多重网格法一样，用于求解障碍问题时，算法的收敛速度分析存在一定的困难［11，13，14］对于障碍问题，一般的收敛性证明都是建立在证明算法产生的序列为一个极小化序列的基础之上［‘，‘’，“…     

MORTAR型旋转Q_1元的多重网格方法

本文讨论了mortar型旋转Q_1元的多重网格方法.证明了W循环的多重网格法是最优的,即收敛率与网格尺寸及层数无关.同时给出了一种可变的V循环多重网格算法,得到了一个条件数一致有界的预条件子.最后,数值试验验证了我们的理论结果.     

非协调Wilson有限元的多重网格方法

§1.引言 非协调Wilson有限元[1—3]对解弹性力学方程有实用价值,在工程上有用。本文分析Wilson元的多重网格法,给出用多重网格方法求得的近似解按L~2模和能量模的最佳收敛阶误差估计。对于W-循环,可以证明其计算量与离散空间的维数为同一量级O(N_k)。 考虑二阶椭圆Dirchlet边值问题:     

非协调板元的一般性误差估计式

１．引言 薄板弯曲问题对应于４阶椭圆边值问题,协调有限元求解此问题需要单元具有Ｃ~１连续性,这难于构造且应用不便,因此求解该问题主要应用非协调元．当非协调板元不具有 Ｃ０连续性时,标准能量模误差估计是 ,这一结果不理想,因为对一般的区域,甚至是凸多边形区域,真解只能属于 Ｈ３．近年来,企图将真解属于 Ｈ４的假定改为真解属于 Ｈ３的研究引起重视．针对最简单的三角形非协调板元－Ｍｏｒｌｅｙ元,石钟慈［２］在 Ｈ３假定下,直接利用非协调元分析技巧得到弯距和转角的误差估计式．本文将［２］的结果一般化,同时通过修…     

非嵌套有限元的W循环多重网格方法

本文讨论了下述情形：１非嵌套网格；２曲边有限元；３非协调元；４拟协调元；５有限元的型函数有特殊性质，都能导致非嵌套的有限元空间．对一个包括上述情形的问题给出了非嵌套有限元的Ｗ循环多重网格方法，并证明了它的收敛性。     

两类带有确定潜伏期的SEIS传染病模型的分析

通过研究两类带有确定潜伏期的SEIS传染病模型,发现对种群的常数输入和指数输入会使疾病的传播过程产生本质的差异．对于带有常数输入的情形,找到了地方病平衡点存在及局部渐近稳定的阈值,证明了地方病平衡点存在时一定局部渐近稳定,并且疾病一致持续存在．对于带有指数输入的情形,发现地方病平衡点当潜伏期充分小时是局部渐近稳定的,当潜伏期充分大时是不稳定的．     

Problems on matchings and independent sets of a graph

Let $G$ be a finite simple graph. For $X?V\left(G\right)$, the difference of $X$, $d\left(X\right)?\left|X\right|?\left|N\left(X\right)\right|$ where $N\left(X\right)$ is the neighborhood of $X$ and $max\{d\left(X\right):X?V\left(G\right)\}$ is called the critical difference of $G$. $X$ is called a critical set if $d\left(X\right)$ equals the critical difference and $\ker \left(G\right)$ is the intersection of all critical sets. $\mathrm{diadem}\left(G\right)$ is the union of all critical independent sets. An independent set $S$ is an inclusion minimal set with$d\left(S\right)>0$ if no proper subset of $S$ has positive difference.A graph $G$ is called a König–Egerváry graph if the sum of its independence number $\alpha \left(G\right)$ and matching number $\mu \left(G\right)$ equals $\left|V\left(G\right)\right|$.In this paper, we prove a conjecture which states that for any graph the number of inclusion minimal independent set $S$ with $d\left(S\right)>0$ is at least the critical difference of the graph.We also give a new short proof of the inequality $\left|\ker \left(G\right)\right|+\left|\mathrm{diadem}\left(G\right)\right|\le 2\alpha \left(G\right)$.A characterization of unicyclic non-König–Egerváry graphs is also presented and a conjecture which states that for such a graph $G$, the critical difference equals $\alpha \left(G\right)?\mu \left(G\right)$, is proved.We also make an observation about $\ker \left(G\right)$ using Edmonds–Gallai Structure Theorem as a concluding remark.     

基于规模的企业竞争力蜘蛛图法评价研究

科学合理的规模结构不仅是实现规模经济的基本条件,而且是提高经济效益、降低交易成本、获得较高的企业竞争力的重要保证.基于规模理论,从生产规模、资本规模、市场规模以及效益规模四大因素入手,提出了一套基于规模的企业竞争力评价指标体系,运用蜘蛛图法建立了基于规模的企业竞争力评价模型,并结合具体的数据分析说明了企业竞争力的大小强弱.此种方法具有直观形象、定量化、可操作性强的特点.     

Decomposability index of tournaments

Given a tournament $T$, a module of $T$ is a subset $X$ of $V\left(T\right)$ such that for $x,y\in X$ and $v\in V\left(T\right)?X$, $(x,v)\in A\left(T\right)$ if and only if $(y,v)\in A\left(T\right)$. The trivial modules of $T$ are $?$, $\left\{u\right\}$ $(u\in V\left(T\right))$ and $V\left(T\right)$. The tournament $T$ is indecomposable if all its modules are trivial; otherwise it is decomposable. The decomposability index of $T$, denoted by $\delta \left(T\right)$, is the smallest number of arcs of $T$ that must be reversed to make $T$ indecomposable. For $n\ge 5$, let $\delta \left(n\right)$ be the maximum of $\delta \left(T\right)$ over the tournaments $T$ with $n$ vertices. We prove that $?\frac{n+1}{4}?\le \delta \left(n\right)\le ?\frac{n?1}{3}?$ and that the lower bound is reached by the transitive tournaments.     

A sufficient condition for DP-4-colorability

DP-coloring of a simple graph is a generalization of list coloring, and also a generalization of signed coloring of signed graphs. It is known that for each $k\in \{3,4,5,6\}$, every planar graph without $C_k$ is 4-choosable. Furthermore, Jin et al. (2016) showed that for each $k\in \{3,4,5,6\}$, every signed planar graph without $C_k$ is signed 4-choosable. In this paper, we show that for each $k\in \{3,4,5,6\}$, every planar graph without $C_k$ is 4-DP-colorable, which is an extension of the above results.     

Detection of multivariate outliers with location slippage or scale inflation in left orthogonally invariant or elliptically contoured distributions

This paper is concerned with two kinds of multiple outlier problems in multivariate regression. One is a multiple location-slippage problem and the other is a multiple scale-inflation problem. A multi-decision rule is proposed. Its optimality is shown for the first problem in a class of left orthogonally invariant distributions and is also shown for the second problem in a class of elliptically contoured distributions. Thus the decision rule is robust against departures from normality. Further the null robustness of the decision statistic which the rule is based on is pointed out in each problem.     

Efficient exponential-time algorithms for edit distance between unordered trees

The edit distance problem for rooted unordered trees is known to be NP-hard. Based on this fact, this paper studies exponential-time algorithms for the problem. For a general case, an $O(\min ({1.26}^{n_1+n_2},2^{b_1+b_2}\cdot \text{<mi mathvariant="italic" is="true">poly</mi>}(n_1,n_2)))$ time algorithm is presented, where $n_1$ and $n_2$ are the numbers of nodes and $b_1$ and $b_2$ are the numbers of branching nodes in two input trees. This algorithm is obtained by a combination of dynamic programming, exhaustive search, and maximum weighted bipartite matching. For bounded degree trees over a fixed alphabet, it is shown that the problem can be solved in $O({(1+ϵ)}^{n_1+n_2})$ time for any fixed $ϵ>0$. This result is achieved by avoiding duplicate calculations for identical subsets of small subtrees.     

Steiner tree packing number and tree connectivity

Let $S$ be a set of at least two vertices in a graph $G$. A subtree $T$ of $G$ is a $S$-Steiner tree if $S?V\left(T\right)$. Two $S$-Steiner trees $T_1$ and $T_2$ are edge-disjoint (resp. internally vertex-disjoint) if $E\left(T_1\right)\cap E\left(T_2\right)=?$ (resp. $E\left(T_1\right)\cap E\left(T_2\right)=?$ and $V\left(T_1\right)\cap V\left(T_2\right)=S$). Let ${\lambda }_G\left(S\right)$ (resp. ${\kappa }_G\left(S\right)$) be the maximum number of edge-disjoint (resp. internally vertex-disjoint) $S$-Steiner trees in $G$, and let ${\lambda }_k\left(G\right)$ (resp. ${\kappa }_k\left(G\right)$) be the minimum ${\lambda }_G\left(S\right)$ (resp. ${\kappa }_G\left(S\right)$) for $S$ ranges over all $k$-subset of $V\left(G\right)$. Kriesell conjectured that if ${\lambda }_G\left(\{x,y\}\right)\ge 2k$ for any $x,y\in S$, then ${\lambda }_G\left(S\right)\ge k$. He proved that the conjecture holds for $\left|S\right|=3,4$. In this paper, we give a short proof of Kriesell’s Conjecture for $\left|S\right|=3,4$, and also show that ${\lambda }_k\left(G\right)\ge ?\frac{1}{k?1}?\frac{k?}{2}??$ (resp. ${\kappa }_k\left(G\right)\ge ?\frac{1}{k?1}?\frac{k?}{2}??$ ) if $\lambda \left(G\right)\ge ?$ (resp. $\kappa \left(G\right)\ge ?$) in $G$, where $k=3,4$. Moreover, we also study the relation between ${\kappa }_k\left(L\left(G\right)\right)$ and ${\lambda }_k\left(G\right)$, where $L\left(G\right)$ is the line graph of $G$.