利用子空间划分的局部离群数据挖掘算法

目前大多数局部离群数据挖掘算法需人为事先设置参数或阈值,且难以应用到高维数据集.给出一种新的局部离群数据挖掘算法PSO-SPLOF,该算法首先将数据集划分为互不相交的子空间,利用偏斜度判断子空间划分的优劣,并采用微粒群算法搜索最优划分子空间集;其次针对每个最优划分子空间,计算其数据对象的局部离群因子SPLOF值,并用SPLOF值来度量数据对象的局部偏离程度.最后采用离散化的天体光谱数据作为数据集,实验验证了PSO-SPLOF算法具有受人为因素影响小、伸缩性强和运算效率高等优点.     

结合粒子滤波与Mean shift的高速运动目标跟踪

Mean shift跟踪算法能够有效跟踪视频序列中的各种运动目标,但是该算法无法准确地跟踪视频中高速运动目标.通过分析mean shift算法的原理,指出mean shift对高速运动目标跟踪失效的原因,提出一种基于mean shift的粒子滤波跟踪的新算法.通过实验比较,该算法能改善了Mean shift算法对高速运动目标的效果,并且在存在干扰目标的情况下具备良好的跟踪效果.     

基于动态混沌扰动的粒子群优化及其应用

针对混沌粒子群算法中存在的盲目搜索问题,提出基于动态混沌扰动的粒子群优化算法。对标准粒子群优化引入动态混沌扰动,在最优值改变时进行较小扰动,在多次不变时进行动态扰动范围的混沌扰动,减少混沌粒子群算法中存在的盲目搜索,提高搜索速度和效率,使有限的时间用在最有效的搜索上。将该算法应用到K均值算法中,可以克服K均值算法的局部最优和对初值和孤立点敏感的缺点,使K均值算法得到全局最优解。通过仿真实验证实该算法的高效性和稳定性。     

基于SOPC的望远镜多策略控制器设计

基于NIOS II为核心的可编程片上系统(SOPC),设计可重构的SOPC硬件配置和控制软核,将简单文件传输协议服务器扩展为专门的传输写入服务器,完成远程在线导入多个SOPC硬件配置和控制软核,并制定硬软件远程切换流程,从而实现基于FPGA3C25的多策略控制器设计。在大型望远镜控制系统中的成功应用验证了该设计的可行性。     

Discrete particle swarm optimization based on estimation of distribution for terminal assignment problems

Terminal assignment problem (TEAP) is to determine minimum cost links to form a network by connecting a given set of terminals to a given collection of concentrators. This paper presents a novel discrete particle swarm optimization (PSO) based on estimation of distribution (EDA), named DPSO-EDA, for TEAP. EDAs sample new solutions from a probability model which characterizes the distribution of promising solutions in the search space at each generation. The DPSO-EDA incorporates the global statistical information collected from personal best solutions of all particles into the PSO, and therefore each particle has comprehensive learning and search ability. In the DPSO-EDA, a modified constraint handling method based on Hopfield neural network (HNN) is also introduced to fit nicely into the framework of the PSO and thus utilize the merit of the PSO. The DPSO-EDA adopts the asynchronous updating scheme. Further, the DPSO-EDA is applied to a problem directly related to TEAP, the task assignment problem (TAAP), in order to show that the DPSO-EDA can be generalized to other related combinatorial optimization problems. Simulation results on several problem instances show that the DPSO-EDA is better than previous methods.     

Checking determinism of XML Schema content models in optimal time

We consider the determinism checking of XML Schema content models, as required by the W3C Recommendation. We argue that currently applied solutions have flaws and make processors vulnerable to exponential resource needs by pathological schemas, and we help to eliminate this potential vulnerability of XML Schema based systems. XML Schema content models are essentially regular expressions extended with numeric occurrence indicators. A previously published polynomial-time solution to check the determinism of such expressions is improved to run in linear time, and the improved algorithm is implemented and evaluated experimentally. When compared to the corresponding method of a popular production-quality XML Schema processor, the new implementation runs orders of magnitude faster. Enhancing the solution to take further extensions of XML Schema into account without compromising its linear scalability is also discussed.     

Soft groups and normalistic soft groups

Soft set theory, proposed by Molodtsov, has been regarded as an effective mathematical tool to deal with uncertainties. In this paper, first we correct some of the problematic cases in a previous paper by Akta? and Çag˜man [H. Akta?, N. Çag˜man, Soft sets and soft groups, Inf. Sci. 177 (2007) 2726-2735]. Moreover, we introduce the concepts of normalistic soft group and normalistic soft group homomorphism, study their several related properties, and investigate some structures that are preserved under normalistic soft group homomorphisms.     

Soft polygroups

Soft set theory, introduced by Molodtsov, has been considered as an effective mathematical tool for modeling uncertainties. In this paper, we initiate the study of algebraic hyperstructures of soft sets. The concepts of soft polygroups, normal soft polygroups, soft subpolygroups and normal soft subpolygroups are introduced, and some related properties are investigated. Furthermore, we propose the homomorphism and isomorphism of soft polygroups, and establish three isomorphism theorems for soft polygroups.     

Low-complexity joint transmit and receive antenna selection for MIMO systems

In this paper, we present a low-complexity algorithm for real-time joint transmit and receive antenna selection in MIMO systems. The computational complexity of exhaustive search in this problem grows exponentially with the number of transmit and receive antennas. We apply Binary Particle Swarm Optimization (BPSO) to the joint transmit and receive antenna selection problem. In addition, applying the general BPSO to joint antenna selection, we also present a specific improvement to this population-based heuristic algorithm, namely, we feed cyclically shifted initial population so that the average convergence time (the number of iterations until reaching an acceptable solution) is reduced. The proposed BPSO for joint antenna selection problem has a low computational complexity, and its effectiveness is verified through simulation results.     

基于改进PSO算法的测试数据自动生成研究

为了提高软件测试中测试数据自动生成的效率,提出了一种基于改进PSO算法的测试数据自动生成的方法。通过在标准的PSO算法中引入人工免疫的思想,保持了群体的多样性,从而有效避免标准PSO算法易陷入局部最优的问题,提高了算法全局搜索的能力,增强了算法的整体性能。实验结果表明,利用改进后的PSO算法寻找最优解所需的迭代次数和时间明显少于标准粒子群算法,生成测试数据的速度快、效率高。