非正则线性增广拉格朗日乘子法的收敛速率研究CSCD

Recently,an indefinite linearized augmented Lagrangian method(IL-ALM)was proposed for the convex programming problems with linear constraints.The IL-ALM differs from the linearized augmented Lagrangian method in that the augmented Lagrangian is linearized by adding an indefinite quadratic proximal term.But,it preserves the algorithmic feature of the linearized ALM and usually has the advantage to improve the performance.The IL-ALM is proved to be convergent from contraction perspective,but its convergence rate is still missing.This is mainly because that the indefinite setting destroys the structures when we directly employ the contraction frameworks.In this paper,we derive the convergence rate for this algorithm by using a different analysis.We prove that a worst-case O(1/t)convergence rate is still hold for this algorithm,where t is the number of iterations.Additionally we show that the customized proximal point algorithm can employ larger step sizes by proving its equivalence to the linearized ALM.     

An artificial hummingbird algorithm based localization with reduced number of reference nodes for wireless sensor networks

Wireless Sensor Networks (WSN) are widely used in recent years due to the advancements in wireless and sensor technologies. Many of these applications require to know the location information of nodes. This information is useful to understand the collected data and to act on them. Existing localization algorithms make use of a few reference nodes for estimating the locations of sensor nodes. But, the positioning and utilization of reference nodes increase the cost and complexity of the network. To reduce the dependency on reference nodes, in this paper, we have developed a novel optimization based localization method using only two reference nodes for the localization of the entire network. This is achieved by reference nodes identifying a few more nodes as reference nodes by the analysis of the connectivity information. The sensor nodes then use the reference nodes to identify their locations in a distributive manner using Artificial Hummingbird Algorithm (AHA). We have observed that the localization performance of the reported algorithm at a lower reference node ratio is comparable with other algorithms at higher reference node ratios.     

Performance guarantees of forward and reverse greedy algorithms for minimizing nonsupermodular nonsubmodular functions on a matroid

This letter studies the problem of minimizing increasing set functions, equivalently, maximizing decreasing set functions, over the base matroid. This setting has received great interest, since it generalizes several applied problems including actuator and sensor placement problems in control, task allocation problems, video summarization, and many others. We study two greedy heuristics, namely, the forward and reverse greedy. We provide two novel performance guarantees for the approximate solutions obtained by them depending on both submodularity ratio and curvature.     

基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GA_XGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采...     

零误差计算

研究采用有误差的数值计算来获得无误差的准确值具有重要的理论价值和应用价值.这种通过近似的数值方法获得准确结果的计算被称为零误差计算.本文首先指出,只有一致离散集合中的数才能够开展零误差计算,即有非零隔离界的数集,这也是数可以进行零误差计算的一个充要条件.以此为基本出发点,本文分析代数数零误差计算的最低理论精度,该精度对应于恢复近似代数数的准确值时必要的误差控制条件,但由于所采用恢复算法的局限性,这一理论精度往往不能保证成功恢复出代数数的准确值.为此,本文给出采用PSLQ (partial-sum-LQ-decomposition)算法进行代数数零误差计算所需的精度控制条件,与基于LLL (Lenstra-Lenstra-Lovász)算法相比,该精度控制条件关于代数数次数的依赖程度由二次降为拟线性,从而可降低相应算法的复杂度.最后探讨零误差计算未来的发展趋势.     

改进的QGA-ELM算法水稻叶面积指数反演模型

为了通过植被指数(VI)准确、可靠的获取不同施肥梯度、不同品种的水稻叶面积指数(LAI),提出了一种基于改进的QGA-ELM算法应用于水稻LAI反演.首先通过8折交叉验证确定极限学习机(ELM)最佳的隐含层神经元个数与隐含层激活函数类型,再通过引入组合动态旋转角策略、单点混沌交叉操作、混沌变异操作、确定性选择策略、量子...     

10 Gb/s光纤通信系统一阶偏振模色散动态补偿系统反馈控制的实现

在偏振模色散(PMD)自动补偿技术中,如何根据反馈信号得到相应的控制信号,使补偿速度跟随偏振模色散变化始终是该技术的一个核心问题。提出了一种新颖的自适应抖动跟踪算法,完成了以微波信号为反馈的多自由度的一阶偏振模色散自动反馈补偿系统的跟踪补偿实验。算法成功地解决了传统算法在跟踪搜索过程中易陷入局部极值的问题,有效地克服了系统中的重要控制器件偏振控制器的磁滞现象以及动态补偿时跟踪搜索过程中易出现的瞬间恶化现象。实验结果表明该算法在对出现突发偏振模色散扰动后自动进行补偿的响应速度在ms量级,最快能达到1~2 ms。     

二层线性规划的自适应遗传算法

提出了一种自适应遗传算法来求解二层线性规划问题.该方法克服了难以确定合适的交叉概率和变异概率的困难.另外,在该方法中还采用了其它一些技巧不仅解决了在采用遗传算法经常出现的有些个体不可行的问题,而且还改进了算法的效率.     

基于概率加权共轭梯度算法的混凝土超声波层析成像

在混凝土层析成像中,为了提高反演的准确性和计算效率,针对共轭梯度算法提出一种加权算法——概率加权共轭梯度算法.新算法不同于常规的加权算法,权重是加在成像单元上而不是方程上.为取得较好的权重因子和较好的迭代初始值,采用IART算法的权重和迭代初始值的选取方法.模拟算例和混凝土试验均表明这种加权算法的可行性.     

直接驱动柱内爆流体力学不稳定性数值模拟

 给出了LARED-S程序对直接驱动柱内爆流体力学不稳定性模拟的物理方程，介绍了一种直接驱动柱内爆靶的结构，给出了模拟中使用活动网格追踪和其他一些需要注意的问题。对OMEGA激光器直接驱动柱内爆实验物理模型进行了简化处理：使用理想气体状态方程，假设烧蚀层、标识层和内部填充材料为同一介质，只在密度上有差别；采用全电离和单温近似，在内爆过程中仅考虑热传导过程而忽略辐射和非局域电子热传导等过程的影响。模拟结果表明：LARED-S程序与LASNEX程序的计算结果基本上符合。