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.     

Coordinated Bayesian optimal approach for the integrated decision between electronic countermeasure and firepower attack

The coordinated Bayesian optimization algorithm (CBOA) is proposed according to the characteristics of the function independence, conformity and supplementary between the electronic countermeasure (ECM) and the firepower attack systems. The selection criteria are combinations of probabilities of individual fitness and coordinated degree and can select choiceness individual to construct Bayesian network that manifest population evolution by producing the new chromosome. Thus the CBOA cannot only guarantee the effective pattern coordinated decision-making mechanism between the populations, but also maintain the population multiplicity, and enhance the algorithm performance. The simulation result confirms the algorithm validity.     

雷达大地回波反射和散射系数的测量

介绍了雷达大地回波特性的一种测量方法 ,包括测量系统框图和基于回波波形的数据处理方法。利用该方法得出了一种地面的反射系数和散射系数 ,该结果对雷达高度表的设计和其它地面反射和散射系数测量均具有参考价值     

一种复杂系统研究方法——基于多智能体的整体建模仿真方法

本文在对一般复杂系统进行研究分析的基础上,针对目前国内外的研究现状,提出了一种研究复杂系统的新方法－基于多智能体的整体建模仿真方法,对这种方法的操作流程和步骤进行了详细的说明,并介绍了支撑这种方法的ＳＷＡＲＭ仿真平台,最后指出了这种建模仿真方法在军事和经济系统中的应用前景。     

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.     

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.     

System deployment optimization in architecture design

Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first formulates a mathematical model to theorize and operationalize the SDO problem and then identifies optimal so- lutions to solve the SDO problem. In the solutions, the success rate of the combat task is maximized, whereas the execution time of the task and the cost of changes in the system structure are mini- mized. The presented optimized algorithm generates an optimal solution without the need to check the entire search space. A novel method is finally proposed based on the combination of heuristic method and genetic algorithm （HGA）, as well as the combination of heuristic method and particle swarm optimization （HPSO）. Experi- ment results show that the HPSO method generates solutions faster than particle swarm optimization （PSO） and genetic algo- rithm （GA） in terms of execution time and performs more efficiently than the heuristic method in terms of determining the best solution.     

新型掺铒硼铋锶酸盐玻璃的J-O参数计算

用高温熔融法制备了成分为：B2O3-Bi2O3-SrO的新型掺铒硼铋锶酸盐玻璃．测试了样品的发射光谱和吸收光谱．利用Judd—Ofelt理论计算了该玻璃样品的J-O参数（Ω2,Ω4,Ω6）和Er^3＋各相关能级的理论振子强度、实验振子强度等发光参数,并对其发光特性进行了研究．计算结果表明：该硼铋锶酸盐玻璃的共价性强于已被报道的大多数玻璃,且其跃迁几率最大的两个能级为^4I13/2和^4I15／2能级．     

对流热过程数值计算稳定性关系新探讨(I)--耗散熵产非负定性分析

探讨性地定义了广义熵的概念;对于给定的模型方程,建立了相应的熵方程,揭示了模型方程潜在固有的耗散熵产非负定性质;提出了以该非负定性为准则,对模型方程的一般化数据格式稳定性限制条件的分析方法.针对一些典型的数值格式导出了具体的限制性条件,归纳性地显示该方法的结果为稳定性的充分条件,为耗散与数值稳定性的内在联系提供了新的理解.     

再生核空间中时间分数阶扩散方程的数值解法

提出一种简单的求解时间分数阶扩散方程的新方法,数值结果表明该方法是有效的.