New model for load-sharing k-out-of-n: G system with different components

On the basis of capacity flow model, a new model is developed for a load-sharing k-out-of-n： G system consisting of different components, to describe the increase of the same component＇s failure rates under different loads. All components have exponential life distributions and are nonrepairable in the system. Reliability of load- sharing 2-out- of-3： G system is calculated and some special cases for the system are discussed. The calculation and discussions show that the model is right and practical.     

基于过度自信的资本市场委托代理关系

从行为金融学角度,将过度自信行为考虑进激励机制及内部监督和外部监督的设计之中,分别研究了过度自信条件下市场微观和宏观层面上委托人与经纪人之间的委托代理关系.结果表明,市场微观层面上,经纪人的过度自信行为与委托人采取的内、外监督措施均可降低代理成本,两者在解决委托人与经纪人之间的代理问题中是相互替代、而不是相互补充的;市场宏观层面上,被雇佣的过度自信经纪人的人数比例,随其整体对市场自信程度的加大而上升.这两个层面所得结论在实际应用中相辅相成,从不同角度为解决资本市场中的代理问题提供了有益思路.     

基于集合距离的信息优势度量方法

当前信息优势度量研究混淆了信息优势及其效能等概念,度量指标缺乏严格数学基础,存在操作性不强、解释力不足、适用范围有限等缺点。针对上述问题,提出了一种基于集合距离的信息优势度量方法,通过引入感知信息集合与客观信息集合的距离度量,重新定义信息质量、信息优势等重要概念。详细讨论了最优子模式分配等几种常用集合距离的选取,并利用基于Agent的同质化协同模型对最优子模式分配距离下的信息质量进行了初步验证。结果表明,该方法具备可操作性,可更好反映信息优势局部和动态特性,且在部分条件下可退化为传统方法,灵活性和兼容性更强。     

一种时空联合约束的多源航迹相似性度量模型

针对传统方法无法有效度量多源异步航迹时空相似性的问题,该文提出了一种适用于多源异步航迹的相似性度量模型。基于时间和空间联合约束下寻找近似时空特征匹配点的思想,通过设置时间和空间阈值上寻找符合要求的匹配点,并通过空间相似函数度量匹配点的相似性,确定最优匹配点并计算多源航迹间的航迹时空相似度。实测数据表明,该模型可以有效度量异类传感器航迹的相似性,且时间性能较优。基于该模型的航迹关联算法在仿真的复杂多目标环境中的关联准确性优于现有算法,且在对海雷达误差估计中得到了应用。     

基于多方向突堤扫描的极化SAR图像人工港口检测

针对现有合成孔径雷达(synthetic aperture radar, SAR)图像中基于海陆两区域分割和单方向突堤扫描港口检测方法存在虚警率高的问题,提出一种基于多区域分割和多方向突堤扫描的人工港口检测方法。该方法首先使用基于极化SAR相干矩阵统计特性的多区域水平集分割方法将地物分割为水域、强散射建筑和其他陆地3类;然后在水陆分割结果上从多对正交方向对沿岸突堤进行扫描,从而确定出港口感兴趣区域;最后利用强散射建筑分割结果实现感兴趣区域中人工港口和虚警天然凸起地形的区分。基于RADARSAT-2对新加坡和湛江地区实际观测的极化SAR数据进行实验,结果表明本文方法较好地实现了沿岸人工港口的正确检测。     

The distributed representation for societal risk classification toward BBS posts

The risk classification of BBS posts is important to the evaluation of societal risk level within a period. Using the posts collected from Tianya forum as the data source, the authors adopted the societal risk indicators from socio psychology, and conduct document-level multiple societal risk classification of BBS posts. To effectively capture the semantics and word order of documents, a shallow neural network as Paragraph Vector is applied to realize the distributed vector representations of the posts in the vector space. Based on the document vectors, the authors apply one classification method KNN to identify the societal risk category of the posts. The experimental results reveal that paragraph vector in document-level societal risk classification achieves much faster training speed and at least 10% improvements of F-measures than Bag-of-Words. Furthermore, the performance of paragraph vector is also superior to edit distance and Lucene-based search method. The present work is the first attempt of combining document embedding method with socio psychology research results to public opinions area.     

A new cascading failure model with delay time in congested complex networks

Cascading failures often occur in congested complex networks. Cascading failures can be expressed as a three-phase process: generation, diffusion, and dissipation of congestion. Different from the betweenness centrality, a congestion function is proposed to represent the extent of congestion on a given node. Inspired by the restart process of a node, we introduce the concept of “delay time,” during which the overloaded node cannot receive or forward any traffic, so an intergradation between permanent removal and nonremoval is built and the flexibility of the presented model is demonstrated. Considering the connectivity of a network before and after cascading failures is not cracked because the overloaded node are not removed from network permanently in our model, a new evaluation function of network efficiency is also proposed to measure the damage caused by cascading failures. Finally, we investigate the effects of network structure and size, delay time, processing ability, and traffic generation speed on congestion propagation. Cascading processes composed of three phases and some factors affecting cascade propagation are uncovered as well.     

Margin optimization algorithm for digital subscriber lines based on particle swarm optimization*

The margin maximization problem in digital subscriber line (DSL) systems is investigated. The particle swarm optimization (PSO) theory is applied to the nonconvex margin optimization problem with the target power and rate constraints. PSO is a new evolution algorithm based on the social behavior of swarms, which can solve discontinuous, nonconvex and nonlinear problems efficiently. The proposed algorithm can converge to the global optimal solution, and numerical example demonstrates that the proposed algorithm can guarantee the fast convergence within a few iterations.     

性能优化的认知无线电网络安全路由选择算法

针对认知无线电网络可用频谱动态变化的特点和认知节点存在有意或无意丢包干扰问题,将跳数最少、鲁棒性强和路由安全等级高作为路由选择标准,提出了一种路由选择算法。跳数最少可简化数据传输过程;鲁棒性强可保证在可用频谱动态变化时,数据稳定传输,提高网络吞吐率;路由安全等级高可以减少由于转发节点存在的有意或无意干扰而引起的数据包丢失。给出了算法的具体实现步骤,理论分析和仿真实验表明该算法是高效和可行的。