A hybrid cuckoo search algorithm with feasibility-based rule for constrained structural optimization

Constrained optimization problems are very important as they are encountered in many science and engineering applications. As a novel evolutionary computation technique, cuckoo search （CS） algorithm has attracted much attention and wide applications, owing to its easy implementation and quick convergence. A hybrid cuckoo pattern search algorithm （HCPS） with feasibility-based rule is proposed for solving constrained numerical and engineering design optimization problems. This algorithm can combine the stochastic exploration of the cuckoo search algorithm and the exploitation capability of the pattern search method. Simulation and comparisons based on several well-known benchmark test functions and structural design optimization problems demonstrate the effectiveness, efficiency and robustness of the proposed HCPS algorithm.     

封闭域UCT算法的实现及其性能测试

UCT算法在9×9棋盘上的水平,已经接近最优秀的专业棋手,但在19×19棋盘上还不尽人意.一种可能的改进是用多个并行的局部UCT搜索来替代全局UCT搜索,以期用同样的计算资源来达到更深的有效搜索深度.本文力图沿着此研究思路做一些初步的尝试.我们通过改写Fuego的全局UCT搜索算法,本文实现了封闭域UCT搜索算法,并在64个封闭域围棋死活问题上进行了测试.初步结果表明,封闭域UCT算法能够在不使用任何领域知识的情况下,把给定问题的初始分支系数从5~16降低到2.3以下.从正确率和速度两项指标来看,多个并行的局部UCT搜索的研究思路具备可行性.     

基于亮度分区的显微镜灰度图像彩色化算法的研究

电子显微镜下细胞成像为灰度图像,不便于观察和研究,由此提出一种电子显微镜下灰度图像的彩色化算法。对彩色和灰度图像的亮度直方图分别进行高次B样条最小二乘曲线拟合,对拟合的曲线分别求取极值点,通过自动地将彩色图像和灰度图像的极值点的个数调整一致,以此作为图像的分区,利用带有权重的颜色迁移算法进行分区映射实现灰度图像的彩色化。实验结果证明,此方法取得了较好的色彩效果。     

流动条件下炔氧甲基季胺盐的缓蚀性能研究

利用交流阻抗(EIS)、线性极化、动电位极化和失重法，研究了炔氧甲基季胺盐对N80在常温CO2饱和的3％NaCl溶液中的电化学行为和缓蚀性能的影响．结果表明：空白溶液中N80的累计失重在4m／s以后急剧增大，即介质的临界流速为4～5m／s．动态下炔氧甲基季胺盐存在与静态下相同的浓度极值现象，流速低于5m／s时缓蚀剂的极值浓度与静态时相同，都为150mg／L，而流速高于5m／s后极值浓度有所增加．     

基于模糊熵与CS-ELM的供输弹系统早期故障识别北大核心

针对供输弹系统早期采集的信号中成分复杂,故障特征难以提取和识别的问题,提出一种基于模糊熵与布谷鸟改进的极限学习机(CS-ELM)的供输弹系统早期故障预示方法。运用改进的可调品质因子小波变换对信号进行滤波降噪,提取各子带信号的模糊熵特征;选取模糊熵值较大的5个子带进行重构,完成降噪并将其模糊熵组成特征向量;运用CS-ELM对所提取的特征向量进行早期故障预示并与ELM的诊断结果进行对比。试验结果验证了该方法的有效性,其预示准确率达90.7%。     

无芯棒拔管拔制力计算─-极值原理的功能平衡法求解

采用极值原理的功能平衡法，确定了无芯棒拔管变形区金属质点的位移和应变增量函数，并按能量原理建立了拔制力的数学模型。经与冷拔钢管的实验比较，本文提供的计算方法可获得较为准确的结果。     

基于云计算的混合并行遗传算法求解最短路径

为提高最短路径求解问题的效率,提出一种基于云计算的细粒度混合并行遗传算法求解最短路径的方法。方法采用云计算中H adoop的Map Reduce并行编程模型,提高编码效率,同时将细粒度并行遗传算法和禁忌搜索算法结合,提高了寻优算法的计算速度和局部寻优能力,进而提高最短路径的求解效率。仿真结果表明,该方法在计算速度和性能上优于经典遗传算法和并行遗传算法,是一种有效的最短路径求解方法。     

基于形态滤波器和中心极值差分的直流电机间接测速

提出了一种基于数学形态学和中心极值差分的直流电机间接测速新方法.首先,在介绍数学形态学理论的基础上,构建了多元素结构并行复合形态滤波器;其次,根据直流电机电流的特点,提出了基于中心极值差分(CED,central extreme difference)的电流频率求取方法;最后根据电机电流频率和转速间的关系,获取了电机的转速特性.较之小波阈值消噪,通过形态学滤波获取的电流曲线较光滑,滤波效果更好;与基于小波脊线的测速方法相比,所提方法不仅获取的转速曲线波动程度较小,而且计算速度也有大幅度的提高.     

Mbius-invariant curve and surface energies and their applications

Curvature-based surface energies are frequently used in mathematics, physics, thin plate and shell engineering, and membrane chemistry and biology studies. Invariance under rotations and shifts makes curvature-based energies very attractive for modeling various phenomena. In computer-aided geometric design, the Willmore surfaces and the so-called minimum variation surfaces （MVS） are widely used for shape modeling purposes. The Willmore surfaces are invariant w.r.t conformal transformations （Mbius or conformal invariance）, and studied thoroughly in differential geometry and related disciplines. In contrast, the minimum variation surfaces are not conformal invariant. In this paper, we suggest a simple modification of the minimum variation energy and demonstrate that the resulting modified MVS enjoy Mbius invariance （so we call them conformal-invariant MVS or, shortly, CI-MVS）. We also study connections of CI-MVS with the cyclides of Dupin. In addition, we consider several other conformal-invariant curve and surface energies involving curvatures and curvature derivatives. In particular, we show how filtering with a conformal-invariant curve energy can be used for detecting salient subsets of the principal curvature extremum curves used by Hosaka and co-workers for shape quality inspection purposes.     

Tabu search algorithm combined with global perturbation for packing arbitrary sized circles into a circular container

The arbitrary sized circle packing problem （ACP） is concerned about how to pack a number of arbitrary sized circles into a smallest possible circular container without overlapping. As a classical NP-hard problem, ACP is theoretically important and is often encountered in practical applications. Based on the already existing Quasi-physical method, this paper proposes a hybrid algorithm named GP-TS which combines tabu search with global perturbation to solve the two-dimensional ACP. The Quasi-physical method is a continuous optimization method which is used to obtain a local optimal configuration from any initial configuration. The tabu search procedure iteratively updates the incumbent configuration with its best neighboring configuration according to some forbidden rule and aspiration criterion. If the configuration obtained by the tabu search procedure does not satisfy the constraints, the global perturbation operator is subsequently applied in order that the search jumps out of the current local optimum without destroying the incumbent configuration too much. After that, the tabu search procedure is launched again. GP-TS is performed by repeating this process until the stop criterion is met. Computational experiments based on 3 sets of representative instances show that GP-TS can improve many best known results within reasonable time.