Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms

We show that biogeography-based optimization (BBO) is a generalization of a genetic algorithm with global uniform recombination (GA/GUR). Based on the common features of BBO and GA/GUR, we use a previously-derived BBO Markov model to obtain a GA/GUR Markov model. One BBO characteristic which makes it distinctive from GA/GUR is its migration mechanism, which affects selection pressure (i.e., the probability of retaining certain features in the population from one generation to the next). We compare the BBO and GA/GUR algorithms using results from analytical Markov models and continuous optimization benchmark problems. We show that the unique selection pressure provided by BBO generally results in better optimization results for a set of standard benchmark problems. We also present comparisons between BBO and GA/GUR for combinatorial optimization problems, include the traveling salesman, the graph coloring, and the bin packing problems.     

Computerized design of advanced straight and skew bevel gears produced by precision forging

The computerized design of advanced straight and skew bevel gears produced by precision forging is proposed. Modifications of the tooth surfaces of one of the members of the gear set are proposed in order to localize the bearing contact and predesign a favorable function of transmission errors. The proposed modifications of the tooth surfaces will be computed by using a modified imaginary crown-gear and applied in manufacturing through the use of the proper die geometry. The geometry of the die is obtained for each member of the gear set from their theoretical geometry obtained considering its generation by the corresponding imaginary crown-gear. Two types of surface modification, whole and partial crowning, are investigated in order to get the more effective way of surface modification of skew and straight bevel gears. A favorable function of transmission errors is predesigned to allow low levels of noise and vibration of the gear drive. Numerical examples of design of both skew and straight bevel gear drives are included to illustrate the advantages of the proposed geometry.     

Improved deterministic algorithms for weighted matching and packing problems

Based on the method of (n,k)-universal sets, we present a deterministic parameterized algorithm for the weighted rd-matching problem with time complexity O^∗(4^{(r−1)k+o(k)}), improving the previous best upper bound O^∗(4^rk+o(k)). In particular, the algorithm applied to the unweighted 3d-matching problem results in a deterministic algorithm with time O^∗(16^k+o(k)), improving the previous best result O^∗(21.26^k). For the weighted r-set packing problem, we present a deterministic parameterized algorithm with time complexity O^∗(2^{(2r−1)k+o(k)}), improving the previous best result O^∗(2^2rk+o(k)). The algorithm, when applied to the unweighted 3-set packing problem, has running time O^∗(32^k+o(k)), improving the previous best result O^∗(43.62^k+o(k)). Moreover, for the weighted r-set packing and weighted rd-matching problems, we give a kernel of size O(k^r), which is the first kernelization algorithm for the problems on weighted versions.     

基于统计证据的半监督多分类器融合方法

针对半监督学习中未标记示例导致性能下降的问题,提出一种新的协同训练算法LDL-tri-training.首先通过最小显著性差异（LSD）假设检验方法使得3个成员分类器两两之间具有显著性差异;然后采用D-S证据理论提高标注的稳定性;最后利用局部异常因子检测算法剔除误标记的噪声样本.实验表明,与其他方法相比,LDL-tri-training算法具有较高的分类精度和稳定性.     

具有网络丢包和时延的网络控制系统设计

为了降低对于网络传输的要求,针对具有固定时延和随机丢包情况的网络系统,采用状态增广以克服时延对网络控制系统分析的影响,进而考虑随机丢包情况,将增广系统转化为切换系统.以此为基础,提出网络鲁棒控制器设计方法.该控制器仅仅基于被控对象的反馈状态,因此对于网络传输的要求较低.最后,通过一个仿真算例验证了该系统的有效性.     

使用二维轮廓线的扩展元球造型技术

提出了一种基于二维轮廓线与超二次曲面型元球模型的造型方法,以实现简单、快速三维模型原型构造.给定一条二维轮廓线,首先使用圆或椭圆去逼近它.然后对每一个圆或椭圆设置第三个维度的参数,能够获得相应的超椭球体型元球.最后混合所有元球的场,并对所有元球的形状参数进行优化,得到一个解析的元球隐式曲面.通过调整元球的位置或形状参数构造出的曲面能够方便地实现形状的修改.模型的不同组成部分可以在不同的投影平面上勾画轮廓线相似地进行设计.该造型方法支持简单的建模操作,如布尔加、减或准扫成体生成,以生成各种复杂形状的模型.此方法能够广泛地应用在计算机图形学或计算机辅助设计领域中的概念设计阶段的原型设计工作中.     

基于智能融合策略的钴离子浓度预测模型

针对湿法炼锌净化过程中钴离子浓度难以准确检测的问题,提出一种基于智能融合策略的钴离子浓度组合预测模型.首先从提高模型预测精度的角度出发,考虑不同核函数对预测性能的影响,分别建立两个在线支持向量回归子模型,并采用改进粒子群优化算法进行子模型参数寻优;然后通过熵值法智能融合策略建立组合预测模型.仿真实验表明,组合模型具有良好的预测性能,预测效果能满足硫酸锌溶液净化过程中对钴离子浓度值的误差要求.     

状态空间模型基于正交梯度搜索的预报误差辨识

提出状态空间模型的正交梯度搜索的预报误差辨识方法.通过极小化输出预报误差而获得系统的参数估计,提出了在观测等价类相切面正交子空间进行参数更新的实现方法,从而解决了全参数化引起的状态空间模型参数非唯一性问题;给出了融合预报误差局部线性逼近性能的正则化因子自适应确定方法,揭示了算法复杂度与系统的能控性、能观测性的内在联系.仿真结果验证了所提出方法的有效性.     

一种改进的PSO网格调度算法

提出了一种基于独立任务的改进PSO网格调度算法(MCPSO)。该算法结合粒子群优化算法和混沌机制,在保证寻优速度的同时又能兼顾"跳出"局部最优的能力。实验结果表明,与基本粒子群优化算法相比,该算法具有更好的收敛速度和求解质量。     

基于MSP430F149与Si4432的无线传感器网络的实现方法

介绍了基于MSP430F149与Si4432的无线传感器网络节点的硬件及软件设计方法,给出了主要的硬件电路和软件流程图,提出了一种简单易实现的低功耗自组织协议。实验证明,该无线传感器网络具有组网速度快、功耗低、抗干扰能力强、通信稳定可靠等特点,可应用于多个领域的信息探测,具有广阔的市场前景。