基于α分布的单矢量传感器多目标方位估计

研究 稳定分布条件下单矢量传感器的多目标方位估计问题。介绍多维 稳定分布特征函数的谱测度表示及谱测度估计方法,在此基础上推导出单矢量传感器输出速度正交分量满足特征函数谱测度表示方程,建立谱测度与目标方位间的对应关系,用特征函数法或一维投影法估计谱测度和目标源方位及数量。仿真结果表明,在 稳定分布假设下,基于谱测度的多目标方位估计法是合理有效的。     

数据流分类变化的分析和检测

针对主动挖掘和被动挖掘2种典型分类方法的特点,分析实际问题中数据流的基本变化类型及衍生的各种变化情况,证明主动挖掘方法在许多情况下无法有效工作,给出一个有效检测数据流变化的思路。采用主动学习方法,利用有限的资源可以组织高质量的类标数据,降低训练数据的需求量。     

日地系统多物理耦合机制的设计与实现

以日地系统活动规律研究为背景,通过对SCIRUN提出的PRMI进行4点改进,提出一种高效的日地系统多物理耦合交互机制PRMI++,能够在物理模型组件进行并行远程方法调用实现耦合交互的同时,自动实现网格重映射和数据并行分布重映射。实验结果证明PRMI++具有较好的性能。     

基于EDK2平台的数据备份与恢复技术

针对文件分配表文件系统数据的安全保障需求,基于符合统一可扩展固件接口(UEFI)规范的EFI开发套件2(EDK2)开源环境,提出一种固件层数据备份与恢复技术。利用EDK2提供协议接口读取硬盘分区数据,将获取的文件及目录信息备份为EFI镜像文件格式,数据恢复时反向写入目标分区。实验结果表明,该技术可解决传统数据备份对操作系统的过度依赖问题,其在固件层实现数据备份,实用性更强。     

基于几何分布的RFID标签数目估算方法

已有的标签数目估算方法准确率低、估算范围小,且标签数目增加时,时隙数目须成比例增加,否则估算误差率将大幅提高。针对上述问题,提出一种基于几何分布的无线射频识别(RFID)标签数目估算方法。在估算标签数目时,将帧长设定为固定值,并在标签中采用多个哈希函数,以减少几何分布偏差,降低估算误差率。实验结果表明,在时间复杂度、空间复杂度不高于其他算法的前提下,该方法能降低估算误差率。     

运输任务分配与路径选择的组合优化模型

针对运输任务分配与路径选择的组合优化问题,提出基于二维染色体结构的改进遗传求解算法。采用自然数编码,设计选择、交叉、变异、检查算子,以及算法的控制参数和算法终止条件,给出遗传算法的求解模型。开发基于C#的实验平台进行验证,结果证明,该算法具有较好的求解性能。     

针对视频会议的一种传输控制方案

为满足视频会议中网络流量的平滑稳定性以及公平竞争性,设计了一种新的传输拥塞控制方案——CTP( Conference Transmission Protocol).CTP在逻辑上分为DCC(Dynamic Congestion Control Layer)和RAC( Rate Amended Control Layer...     

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.     

Estimation of distribution algorithm for permutation flow shops with total flowtime minimization

In this paper, an Estimation of Distribution Algorithm (EDA) is proposed for permutation flow shops to minimize total flowtime. Longest Common Subsequence (LCS) is incorporated into the probability distribution model to mine good “genes”. Different from common EDAs, each offspring individual is produced from a seed, which is selected from the population by the roulette method. The LCS between the seed individual and the best solution found so far is regarded as good “genes”, which are inherited by offspring with a probability less than 100% to guarantee the population diversity. An effective Variable Neighborhood Search (VNS) is integrated into the proposed EDA to further improve the performance. Experimental results show that the inheritance of good “genes” obtained by LCS can improve the performance of the proposed EDA. The proposed hybrid EDA outperforms other existing algorithms for the considered problem in the literature. Furthermore, the proposed hybrid EDA improved 42 out of 90 current best solutions for Taillard benchmark instances.     

Coordination of split deliveries in one-warehouse multi-retailer distribution systems

In this paper, we consider a distribution system where a warehouse is responsible for replenishing the inventories at multiple retailers by a fleet of vehicles of limited capacity. If a distribution policy of the system involves split deliveries, that is, the inventory of at least one retailer is replenished by using multiple vehicle routes, the coordination of the deliveries can further reduce the inventory cost of the retailer. We consider the coordination where two split deliveries are realized by direct shipping and multiple-stop shipping, respectively. To the best of our knowledge, this kind of coordination was never studied in the literature but can find its application in inventory routing problems. This paper proposes and analyses a class of coordination policies for the split deliveries which can reduce the inventory costs of the retailers without increasing transportation costs. A non-linear programming model is established for formulating the class of polices. Because the optimal coordination policy corresponding to an optimal solution of the model may be hard to find and/or implement, two simple but effective coordination policies are proposed. The inventory cost savings realized by the two policies are evaluated analytically and algorithmically. Our theoretical analysis and computational experiments show that both policies are effective. Under certain conditions, they can save 50% of the inventory costs at the retailers without increasing transportation costs.