An algorithmic method for showing existence of nontrivial non-classical symmetries of partial differential equations without solving determining equations

In this paper, based on differential characteristic set theory and the associated algorithm (also called Wu?s method), an algorithmic method is presented to decide on the existence of a nontrivial non-classical symmetry of a given partial differential equation without solving the corresponding nonlinear determining system. The theory and algorithm give a partial answer for the open problem posed by P.A. Clarkson and E.L. Mansfield in [21] on non-classical symmetries of partial differential equations. As applications of our algorithm, non-classical symmetries and corresponding invariant solutions are found for several evolution equations.     

基于卷积神经网络和松鼠优化算法的机翼结构混合优化设计#br#

针对大展弦比机翼的结构轻量化优化设计,提出了一种高效的布局和尺寸混合优化方法．在CFD/CSD气动弹性计算的基础上,对不同的结构变量进行统一编码,使用一维卷积神经网络建立代理模型,并使用松鼠优化算法建立了混合优化模型进行搜索寻优．以某型太阳能无人机的机翼结构优化为例,优化结果表明翼肋的布局变量和翼梁的尺寸变量之间存在着耦合关系,使用松鼠优化算法相比于遗传算法节省了35 %~45 %的计算成本,且混合优化后的结构比原始结构减重4.1 %,验证了该方法的有效性．     

Production lot-sizing with dynamic capacity adjustment

In this paper we study a single-item lot-sizing model in which production capacity can be adjusted from time to time. There are a number of different production capacity levels available to be acquired in each period, where each capacity level is assumed to be a multiple of a base capacity unit. To reduce the waste of excess of capacity but guarantee meeting the demand, it is important to decide which level of capacity should be acquired and how many units of the item should be produced for every period in the planning horizon. Capacity adjustment cost incurs when capacity acquired in the current period differs from the one acquired in the previous period. Capacity acquisition costs, capacity adjustment costs, and production costs in each period are all time-varying and depend on the capacity level acquired in that period. Backlogging is allowed. Both production costs and inventory costs are assumed to be general concave. We provide optimal properties and develop an efficient exact algorithm for the general model. For the special cases with zero capacity adjustment costs or fixed-plus-linear production costs, we present a faster exact algorithm. Computational experiments show that our algorithm is able to solve medium-size instances for the general model in a few seconds, and that cost can be reduced significantly through flexible capacity adjustment.     

条纹相机非线性修正算法

 条纹相机扫描电路的非线性会导致条纹图像时间与强度信息的失真。为了使条纹相机输出图像更加接近实际目标从而得到更高的测量精度,提出一种扫描非线性修正算法。该算法根据给出的标称扫描时间拟合出扫描时间曲线,求出每道的扫描时间,取其算术平均值作为一个标准,根据每道的扫描时间与该标准的数值大小关系来求出每个像素的修正系数,取图像与该系数矩阵的乘积即可完成图像的位置和灰度的修正。实验结果表明可以将测量非线性由原来的8% 减小到2% 以下。     

一种采用相位测量轮廓术的工件在线三维检测方法

提出了一种基于相移轮廓术在线检测工件三维信息的方法.利用计算机编程产生的一固定正弦光栅图通过数字投影机投射在流水线的一段区域,无需专门的相移装置,当物体在线移动穿过此区域时,使用计量光栅等距离定位发信,控制CCD采集五帧变形条纹图,并采用具有一定特征的标记实现五帧变形条纹图间的亚像素级像素匹配,提取相移变形条纹图,由Stoilov算法计算,得到工件表面截断相位,展开后可得到物体表面三维信息.实验验证了其可行性.     

一类特殊矩阵的逆特征值问题

本文主要讨论如下形式矩阵的逆特征值问题:即对给定n个实数λ_1>λ_2>…>λ_2与n-1个实数μ_1>μ_2>…>μ_(n-1),满足λ_1>μ_1>λ_2>…>λ_(n-1)>μ_(n-1)>λ_n,在α_2>α_3>…>α_(n-1)的条件下,存在唯一的一个矩阵A_n是以λ_i为其特征值;且其截边矩阵的特征值为μ_1,μ_2,…,μ_(n-1).     

Cache placement in sensor networks under an update cost constraint

In this paper, we address an optimization problem that arises in the context of cache placement in sensor networks. In particular, we consider the cache placement problem where the goal is to determine a set of nodes in the network to cache/store the given data item, such that the overall communication cost incurred in accessing the item is minimized, under the constraint that the total communication cost in updating the selected caches is less than a given constant. In our network model, there is a single server (containing the original copy of the data item) and multiple client nodes (that wish to access the data item). For various settings of the problem, we design optimal, near-optimal, heuristic-based, and distributed algorithms, and evaluate their performance through simulations on randomly generated sensor networks.     

一种基于遗传算法的图像增强方法

遗传算法是借鉴生物的自然选择和遗传进化机制而开发出的一种全局优化自适应概率搜索算法，目前已在包括图象处理在内的很多领域得到了很好的应用。在图像处理领域，目前的研究主要集中在将遗传算法用于图像分割，图像分类，模式识别等方面。本文将遗传算法用于图像增强，使用图像的参数模型。将图像增强转化为参数的优化，实验结果表明，该方法是一种有效的图像增强方法。     

A projected lagrangian algorithm for semi-infinite programming

A globally convergent algorithm is presented for the solution of a wide class of semi-infinite programming problems. The method is based on the solution of a sequence of equality constrained quadratic programming problems, and usually has a second order convergence rate. Numerical results illustrating the method are given.