防空导弹装备光学伪装效果的集对评估模型

为解决传统光学伪装效果评估指标考虑不全的问题,从敌方侦察能力、装备隐真能力、装备示假能力以及环境四个方面建立了装备光学伪装效果评估指标体系。首先,采用施密特正交马田系统(MTGS)计算指标的权重,不仅考虑了评估者的知识及经验偏好,同时也消除了指标间的信息交互,权重的确定更加合理。然后建立了基于集对分析的评估模型。最后,通过实例验证了评估模型的可靠性。结果表明该模型在装备光学伪装效果评估及伪装器材选取方面具有一定的应用价值。     

The berth allocation optimisation with the consideration of time-varying water depths

Confronting the challenges provided by jumbo container vessels, managers of world-class seaports must take into consideration water depths-related constraints when making the vessel berthing decisions. That is, when the water depths satisfy the requirement of jumbo vessels’ drafts, these vessels are allowed to sail through the navigation channel. In this paper, we study a tactical berth allocation problem under the consideration of time-varying water depths. For the resolution, we propose an integer programming model, a set partitioning formulation and an improved differential evolutionary algorithm. Computational experiments demonstrate that the set partitioning formulation outperforms the integer programming model and can be applied to solve small- and medium-sized problems. The improved differential evolutionary algorithm is recommended for large-sized problems.     

Multi-Rate Polling: Improve the Performance of Energy Harvesting Backscatter Wireless Networks

In recent years, Researchers have proposed the concept of Energy Harvesting Backscatter Wireless Networks (EHBWN). EHBWN usually consists of one sink and several backscatter nodes. Backscatter nodes harvest energy from their environment and communicate with sink through backscattering the carrier wave transmitted by sink. Although a certain amount of access protocols for Energy Harvesting Wireless Networks have been present, they usually do not take the sink’s receiver sensitivity into account, which makes those protocols unsuitable in practice. In this paper, we first give an analysis of the backscatter channel link budget and the relationship between the effective communication range and uplink data rate. After that, we point out that a single uplink data rate for all the backscatter nodes is no longer suitable due to the constraint of sink receiver sensitivity. Later we propose Multi-rate Polling which divides the network into different uplink data rata regions to make sure the correct packet reception by the sink and improve the network performance. Multi-rate Polling also introduces a parameter K, through adjusting it, we can achieve the trade-off between network throughput and fairness to meet the requirement under various scenarios. We validate Multi-rate Polling under different networks and average harvesting rates through simulation. The result shows that the proposed protocol can effectively improve the network performance and has excellent scalability, which makes it suitable for EHBWN.     

基于多特定决策类的不完备决策系统正域约简

现有的属性约简方法大部分关注决策系统中的所有决策类，而在实际决策过程中决策者往往仅关注决策系统中的一种或几种决策类。针对上述问题，提出基于多特定决策类的不完备决策系统正域约简的理论框架。首先，给出不完备决策系统单特定决策类正域约简的概念；第二，将单特定决策类正域约简推广到多特定决策类，构造了相应的差别矩阵及区分函数；第三，分析并证明了相关定理，提出基于差别矩阵的不完备决策系统多特定决策类正域约简算法（PRMDM）；最后，选取4组UCI数据集进行实验。在数据集Teaching-assistant-evaluation、House、Connectionist-bench和Cardiotocography上，基于差别矩阵的不完备决策系正域约简算法（PRDM）的平均约简长度分别为4.00、13.00、9.00和20.00，PRMDM算法（多特定决策类中决策类数目为2）的平均约简长度分别为3.00、8.00、8.00和18.00。实验结果验证了PRMDM算法的有效性。     

基于间隔理论的过采样集成算法

针对传统集成算法不适用于不平衡数据分类的问题，提出基于间隔理论的AdaBoost算法（MOSBoost）。首先通过预训练得到原始样本的间隔；然后依据间隔排序对少类样本进行启发式复制，从而形成新的平衡样本集；最后将平衡样本集输入AdaBoost算法进行训练以得到最终集成分类器。在UCI数据集上进行测试实验，利用F-measure和G-mean两个准则对MOSBoost、AdaBoost、随机过采样AdaBoost（ROSBoost）和随机降采样AdaBoost（RDSBoost）四种算法进行评价。实验结果表明，MOSBoost算法分类性能优于其他三种算法，其中，相对于AdaBoost算法，MOSBoost算法在F-measure和G-mean准则下分别提升了8.4%和6.2%。     

Soft information set for multicriteria decision making

An information source value is perceived differently by different agents. In this paper, we present a new knowledge representation structure, termed as soft information set (SIS), to provide a parameterized representation of the information values, as perceived by an agent. The properties of SIS are investigated and the notion of relations in SIS is devised. The significance of the proposed SIS in aiding multi criteria decision making is illustrated through real case-studies.     

MooseFS热备元数据节点设计与实现

针对MooseFS元数据节点的单点故障问题，对MooseFS源码进行改造，为其增加一个热备的备元数据节点，并通过主备之间同步元数据，备节点回放操作日志等技术使得备元数据节点内存中的元数据时刻跟主元数据节点保持一致。当主元数据节点发生故障切换到备元数据节点后，备元数据节点无需从本地加载元数据即可快速接替主元数据节点对外提供服务。测试结果表明，备元数据节点本地和内存中的元数据均与主元数据节点保持一致，且故障恢复时间小于1 s。     

Möbius变换下四次有理抛物-PH曲线的C2 Hermite插值

目的 曲线插值问题在机器人设计、机械工业、航天工业等诸多现代工业领域都有广泛的应用，而已知端点数据的Hermite插值是计算机辅助几何设计中一种常用的曲线构造方法，本文讨论了一种偶数次有理等距曲线，即四次抛物-PH曲线的C² Hermite插值问题。方法 基于M bius变换引入参数，利用复分析的方法构造了四次有理抛物-PH曲线的C² Hermite插值，给出了具体插值算法及相应的Bézier曲线表示和控制顶点的表达式。结果 通过给出"合理"的端点插值数据，以数值实例表明了该算法的有效性，所得12条插值曲线中，结合最小绝对旋转数和弹性弯曲能量最小化两种准则给出了判定满足插值条件最优曲线的选择方法，并以具体实例说明了与其他插值方法的对比分析结果。结论 本文构造了M bius变换下的四次有理抛物-PH曲线的C² Hermite插值，在保证曲线次数较低的情况下，达到了连续性更高的插值条件，计算更为简单，插值效果明显，较之传统奇数次PH曲线具有更加自然的几何形状，对偶数次PH曲线的相关研究具有一定意义。     

大数据流式计算框架Heron环境下的流分类任务调度策略

新型大数据流式计算框架Apache Heron默认使用轮询调度算法进行任务调度，忽略了拓扑运行时状态以及任务实例间不同通信方式对系统性能的影响。针对这个问题，提出Heron环境下流分类任务调度策略（DSC-Heron），包括流分类算法、流簇分配算法和流分类调度算法。首先通过建立Heron作业模型明确任务实例间不同通信方式的通信开销差异；其次基于流分类模型，根据任务实例间实时数据流大小对数据流进行分类；最后将相互关联的高频数据流整体作为基本调度单元构建任务分配计划，在满足资源约束条件的同时尽可能多地将节点间通信转化为节点内通信以最小化系统通信开销。在包含9个节点的Heron集群环境下分别运行SentenceWordCount、WordCount和FileWordCount拓扑，结果表明DSC-Heron相对于Heron默认调度策略，在系统完成时延、节点间通信开销和系统吞吐量上分别平均优化了8.35%、7.07%和6.83%；在负载均衡性方面，工作节点的CPU占用率和内存占用率标准差分别平均下降了41.44%和41.23%。实验结果表明，DSC-Heron对测试拓扑的运行性能有一定的优化作用，其中对接近真实应用场景的FileWordCount拓扑优化效果最为显著。