《数据结构》教学改革探索

《数据结构》是计算机相关专业的主干课程之一。为了提高教学质量,除了采用传统的行之有效的教学方法之外,还应当采用一些有本课程特色的教学方法,如:面向对象的教学方法,基于数学推导的教学方法和针对重点与难点的讨论式教学方法等。     

利用赫夫曼树建立最佳判定算法

数据结构是计算机程序设计的重要理论技术基础,在软件开发中选择好正确的数据存储结构和算法是关键。赫夫曼树在程序开发和工程中均有较高的使用价值,通过实例介绍了在软件开发中如何利用赫夫曼树建立最佳判定算法,从而提高程序的执行速度。     

基于离散对数体制的大数模幂乘算法的软件实现方法

通过对离散对数体制中DL及DSA算法的描述,分析了在该体制中大量应用的y=xe（m od p）的求解方法,将大数模幂乘算法化整为零,分解成三个相对独立的算法,该方法化简了求y=xe（m od p）的过程,特别适合软件实现.     

A statistical information-based clustering approach in distance space

Clustering, as a powerful data mining technique for discovering interesting data distributions and patterns in the underlying database, is used in many fields, such as statistical data analysis, pattern recognition, image processing, and other business applications. Density-based Spatial Clustering of Applications with Noise (DBSCAN) (Ester et al., 1996) is a good performance clustering method for dealing with spatial data although it leaves many problems to be solved. For example,DBSCAN requires a necessary user-specified threshold while its computation is extremely time-consuming by current method such as OPTICS, etc. (Ankerst et al., 1999), and the performance of DBSCAN under different norms has yet to be examined. In this paper, we first developed a method based on statistical information of distance space in database to determine the necessary threshold. Then our examination of the DBSCAN performance under different norms showed that there was determinable relation between them. Finally, we used two artificial databases to verify the effectiveness and efficiency of the proposed methods.     

SOR算法在计算机上的实现

SOR算法是解线性方程组的迭代加速方法,通过选择恰当的松弛因子ω,它能使收敛速度较慢的迭代法变的收敛快,使发散的迭代法可能变成收敛,因此SOR算法有极高的应用价值.文章提供了SOR算法设计和分析,使得SOR算法能在计算机上高效执行.     

一种基于神经网络级联算法的软件可靠性增长预测方法

介绍了一种基于神经网络级联算法的软件可靠性增长预测方法,阐述了该算法的具体步骤.对预测系统进行了定义,提出了预测手段,并对预测进行了度量.测试结果与传统方法比较,该方法的较优越性能.     

三维直线插补算法的优化及精度分析

优化了最小偏差三维直线插补算法，并在最小偏差法二维直线插补精度不大于半个脉冲当量的基础上．首次采用解析法证明了最小偏差法三维直线插补精度，并用实例进行了验证。为三维直线插补算法的广泛应用奠定了理论基础。     

Application of stochastic method to optimum design of energy-efficient induction motors with a target of LCC

For an energy-efficient induction machine, the life-cycle cost (LCC) usually is the most important index to the consumer. With this target, the optimization design of a motor is a complex nonlinear problem with constraints. To solve the problem, the authors introduce a united random algorithm. At first, the problem is divided into two parts, the optimal rotor slots and the optimization of other dimensions. Before optimizing the rotor slots with genetic algorithm (GA), the second part is solved with TABU algorithm to simplify the problem. The numerical results showed that this method is better than the method using a traditional algorithm. Project (No. 601299) supported by the Science Foundation of Hebei Province, China.     

模糊推理基本算法的数学基础

Algorithm of fuzzy reasoning has been successful applied in fuzzy control, but its theoretical foundation of algorithms has not been thoroughly investigated. In this paper, structure of basic algorithms of fuzzy reasoning was studied, its rationality was discussed from the viewpoint of logic and mathematics, and three theorems were proved. These theorems shows that there always exists a mathematical relation (that is, a bounded real function) between the premises and the conclusion for fuzzy reasoning, and in fact various algorithms of fuzzy reasoning are specific forms of this function. Thus these results show that algorithms of fuzzy reasoning are theoretically reliable.     

基于并行模拟退火算法的TSP问题求解

针对标准模拟退火算法串行优化单个解，优化过程较长、效率较低的弱点，提出一种基于多种群群体优化的并行机制。该机制通过将单个解的串行优化转化为许多个解同时进行的并行优化来提高算法的整体优化效率。利用该算法求解TSP问题能够显著提高优化效率，仿真结果表明该算法是有效的。