分数阶抛物方程控制系统最优控制的稳定性

本文研究了一类分数阶抛物方程的最优控制问题,主要讨论了其最优控制与最优值的稳定性.利用了凸方法获得了获得了这类问题最优控制的稳定性结果,并且推广了在参考文献[3]中的最优控制稳定性结论.     

求解资源受限项目调度问题的人工鱼群算法

提出了将人工鱼群算法应用于求解资源受限项目调度问题中的构想,建立了求解资源受限项目调度问题的人工鱼群算法模型,设计了一种标准随机键编码方式,构建了人工鱼的觅食行为、聚群行为、追尾行为和随机行为四种基本算子,采用了正向逆向局部改进技术和精英保留策略,并给出了算法流程。应用PSPLIB标准问题库对该算法进行了大量的测试,并与其他算法进行了比较,验证了该算法的有效性。     

网络安全产品研究

本文在研究了网络安全的国内外有关情况后对网络安全技术进行了探讨 ,介绍了一种简单而实用的网络安全产品 ,添补了这方面的空白 ,而且本文介绍的产品已经应用到了许多部门 ,为网络安全做出了贡献     

一个函数不等式的加强与延伸

从一个常见的不等式谈起,分析了多种证明方法,运用该不等式推导出了多个重要结论,对不等式进行了扩充和加强,解释了蕴含的意义,显示了该不等式的重要性和深刻性.     

系统动力学在城市污水再生回用系统中的应用

用系统动力学方法研究了城市污水回用系统.首先分析了影响城市污水回用系统的诸多因素以及它们之间的相互关系,探讨了污水再生回用系统行为和结构的特点,确定了系统中因素之间的定量关系,建立了城市污水回用系统动力学(SD)模型,并介绍了模型的检验方法.同时给出了SD模型的具体应用实例,对西北地区的某一城市的污水回用进行了预测和分析,提出了符合该城市发展的污水回用方案.     

交通运输系统协调发展理论与模型研究

提出了交通运输系统协调度的评价分析模型.从系统论的观点出发,提出了交通运输系统协调理论的概念,探讨了交通运输系统随时间而不断演化变迁的规律,给出了交通运输系统协调发展基本步骤;并根据协调学原理,讨论了交通运输系统的协调性问题,提出了系统协调发展模型,对交通运输子系统内部及子系统之间及系统整体的协调发展问题进行了研究,探讨了交通运输可持续发展的系统协调管理过程,为进一步研究交通运输系统的可持续发展奠定了基础.     

一个游戏难题的推广、建模及求解

推广了RPG游戏中的一个难题,建立了相应的数学模型,给出了完善的解决方案,深化了现行的相关结果.     

不同参数下Galton板实验的探讨及仿真

介绍了 Galton板实验的实验现象和物理背景 ,建立了细致的概率模型对实验进行了分析 ,并基于模型对不同参数下的 Galton板实验进行了探讨 ,还利用 MATLAB编制了仿真软件 ,对结论进行了验证 .     

关于举办2012年中学生数学奥林匹克夏令营活动的启事

从1996年至今,华中师范大学数学与统计学学院已成功举办多届全国中学生数学奥林匹克夏令营活动,培养了大批优秀的数学竞赛选手,他们经过权威名师的指点,既丰富了理论知识,更掌握了实践经验,为走上成功明确了航向,在国内、国际数学竞赛中取得了令人瞩目的成绩。我院已成为全国数学奥林匹克活动的重要培训基地,吸引了众多优秀中学生云集武汉参     

基于粗糙集的患者满意度评价模型及其实证分析

在文献阅读及实地调研的基础上,本文提出了患者满意度的定义,建立了影响患者满意度的指标体系,介绍了粗糙集的相关概念及利用粗糙集进行评价的步骤,提出了新的约简方法,构建了基于粗糙集的患者满意度评价模型并进行了实证分析,得出了影响患者满意度的关键指标,并计算了关键指标权重,对江西省十个医院进行了综合评价值的计算.     

A note on parallel depth first search

The subject of this note is the parallel algorithm for depth first searching of a directed acyclic graph by Ghosh and Bhattacharjee. It is pointed out that their algorithm does not always work. A counter example is given. This paper also states the necessary and sufficient condition for the algorithm to fail, or to work correctly.     

Nonlinear Smoothing and the EM Algorithm for Positive Integral Equations of the First Kind

We study a modification of the EMS algorithm in which each step of the EMS algorithm is preceded by a nonlinear smoothing step of the form , where S is the smoothing operator of the EMS algorithm. In the context of positive integral equations (à la positron emission tomography) the resulting algorithm is related to a convex minimization problem which always admits a unique smooth solution, in contrast to the unmodified maximum likelihood setup. The new algorithm has slightly stronger monotonicity properties than the original EM algorithm. This suggests that the modified EMS algorithm is actually an EM algorithm for the modified problem. The existence of a smooth solution to the modified maximum likelihood problem and the monotonicity together imply the strong convergence of the new algorithm. We also present some simulation results for the integral equation of stereology, which suggests that the new algorithm behaves roughly like the EMS algorithm. Accepted 1 April 1997     

An efficient and numerically correct algorithm for the 2D convex hull problem

An efficient and numerically correct program called FastHull for computing the convex hulls of finite point sets in the plane is presented. It is based on the Akl-Toussaint algorithm and the MergeHull algorithm. Numerical correctness of the FastHull procedure is ensured by using special routines for interval arithmetic and multiple precision arithmetic. The FastHull algorithm guaranteesO(N logN) running time in the worst case and has linear time performance for many kinds of input patterns. It appears that the FastHull algorithm runs faster than any currently known 2D convex hull algorithm for many input point patterns.     

Corrections to Lee's visibility polygon algorithm

We present a modification and extension of the (linear time) visibility polygon algorithm of Lee. The algorithm computes the visibility polygon of a simple polygon from a viewpoint that is either interior to the polygon, or in its blocked exterior (the cases of viewpoints on the boundary or in the free exterior being simple extensions of the interior case). We show by example that the original algorithm by Lee, and a more complex algorithm by El Gindy and Avis, can fail for polygons that wind sufficiently. We present a second version of the algorithm, which does not extend to the blocked exterior case.This work was partially supported by grants from the Central Research Fund of the University of Alberta and the Natural Sciences and Engineering Research Council of Canada.     

Minimal perfect hashing in polynomial time

We present a universally applicable algorithm for generating minimal perfect hashing functions. The method has (worst case) polynomial time complexity in units of bit operations. An adjunct algorithm for reducing parameter magnitudes in the generated hash functions is given. This probabilistic method makes hash function parameter magnitudes independent of argument (input key) magnitudes.     

AHP最小二乘排序方法及其算法研究

本文研究AHP中的最小二乘排序方法(LSM)及其算法实现,给出了一种简单的收敛性迭代算法,并进行了理论分析和仿真运算。     

Formal neighbourhoods, combinatory Böhm trees, and untyped normalization by evaluation

We prove the correctness of an algorithm for normalizing untyped combinator terms by evaluation. The algorithm is written in the functional programming language Haskell, and we prove that it lazily computes the combinatory Böhm tree of the term. The notion of combinatory Böhm tree is analogous to the usual notion of Böhm tree for the untyped lambda calculus. It is defined operationally by repeated head reduction of terms to head normal forms. We use formal neighbourhoods to characterize finite, partial information about data, and define a Böhm tree as a filter of such formal neighbourhoods. We also define formal topology style denotational semantics of a fragment of Haskell following Martin-Löf, and let each closed program denote a filter of formal neighbourhoods. We prove that the denotation of the output of our algorithm is the Böhm tree of the input term. The key construction in the proof is a “glueing” relation between terms and semantic neighbourhoods which is defined by induction on the latter. This relation is related to the glueing relation which was earlier used for proving the correctness of normalization by evaluation algorithm for typed combinatory logic.     

An optimal time algorithm for finding a maximum weight independent set in a tree

The maximum weight independent set problem for a general graph is NP-hard. But for some special classes of graphs, polynomial time algorithms do exist for solving it. Based on the divide-and-conquer strategy, Pawagi has presented anO(|V|log|V|) time algorithm for solving this problem on a tree. In this paper, we propose anO(|V|) time algorithm to improve Pawagi's result. The proposed algorithm is based on the dynamic programming strategy and is time optimal within a constant factor.     

Parallel generation of permutations and combinations

In this paper we will present a parallel algorithm to generate the permutations of at mostk out ofn objects. The architecture consists of a linear processor array and a selector. When one single processor array is available, a parallel algorithm to generate permutations is presented which achieves the best possible speedup for any givenk. Also, this algorithm can easily be modified to generate combinations. When multiple processor arrays are available, a parallel scheme is proposed to speed up the generation by fully utilizing these processor arrays. The degree of parallelism is related to the number of available processor arrays.     

A note on optimal multiway split trees

Split trees are suitable data structures for storing records with different access frequencies. Under assumption that the access frequencies are all distinct, Huang has proposed anO(n ⁴ logm) time algorithm to construct an (m+1)-way split tree for a set ofn keys. In this paper, we generalize Huang's algorithm to deal with the case of non-distinct access frequencies. The technique used in the generalized algorithm is a generalization of Hesteret al.'s, where the binary case was considered. The generalized algorithm runs inO(n ⁵ logm) time.