一种基于触发机制的轮转算法

在负载平衡技术中,必须使用合适的算法进行成员选择,以决定由哪个副本对象处理到来的客户请求。传统轮转负载平衡算法只能在某些特定条件下平衡负载。针对该缺点,结合普通轮转算法和加权算法的优点,提出一种基于触发机制的轮转算法。实验结果表明,该算法能感知后段资源。     

WSN中基于LEACH的多层分簇路由方案

针对传统分簇路由中存在的节点能耗严重失衡问题,提出一种新的成簇路由方案。在参考LEACH路由算法的基础上,融合多层分簇的思想,通过在网络拓扑的底层构建具有多个簇头节点的簇集合、在拓扑的顶层构建多跳转发机制,提出能量高效的多层分簇路由算法。仿真结果表明,该算法在网络生存时间和负载均衡方面较已有算法有较大的提高。     

HK网络演化模型的研究和改进

研究一种高集聚度的无标度网络模型,以Holme和Kim（HK）模型为基础,通过引进新增节点所应该具备的连接动态性,改进HK模型的局部特性。分析和仿真表明,改进模型HK’不仅继承了HK模型的高聚类效应和无标度特性,且它的幂律指数可在2～3之间变化,网络成员间的竞争机制也与现实社会网络较接近。     

文献中的词语分布、词型等级和风格计算

文献的语言风格是作者在语言运用方面的思维定势的体现,对于文献之间语言风格的差异,以前的研究大多采用定性分析的方式加以比较和概括,而在文献检索和文本分类领域需要得到量化的语言风格相似度。该文首先分析文献中词语分布的普遍规律,以先秦八部经典文献为观察语料,发现这些文献中的词语既呈离散分布,又呈集中分布;然后通过计算文献之间词型等级的相关系数,来获取量化的语言风格相似度,构建了八部文献之间的相似度矩阵,验证了语言风格的差异不仅体现在使用的常用词上,还更细微地体现在常用词的使用频率等级上。     

A method for stochastic multiple criteria decision making based on dominance degrees

This paper proposes a method for solving the stochastic multiple criteria decision making (SMCDM) problem, where consequences of alternatives with respect to criteria are represented by random variables with probability distributions. Firstly, definitions and related analysis of dominance degree of one probability distribution over another are given. Then, by calculating the dominance degrees, the dominance degree matrix of alternative pairwise comparisons with respect to each criterion is built. Further, using PROMETHEE II method, an overall dominance degree matrix of alternative pairwise comparisons is constructed, and a net flow of each alternative is calculated. Based on the obtained net flows, a ranking of alternatives is determined. Finally, numerical examples for the three cases are given to illustrate the use of the proposed method.     

Univariate marginal distribution algorithm dynamics for a class of parametric functions with unitation constraints

In this paper, we introduce a mathematical model for analyzing the dynamics of the univariate marginal distribution algorithm (UMDA) for a class of parametric functions with isolated global optima. We prove a number of results that are used to model the evolution of UMDA probability distributions for this class of functions. We show that a theoretical analysis can assess the effect of the function parameters on the convergence and rate of convergence of UMDA. We also introduce for the first time a long string limit analysis of UMDA. Finally, we relate the results to ongoing research on the application of the estimation of distribution algorithms for problems with unitation constraints.     

Application of fuzzy sets to manufacturing/distribution planning decisions in supply chains

In the real-world manufacturing/distribution planning decision (MDPD) integration problems in supply chains, the environmental coefficients and parameters are normally imprecise due to incomplete and/or unavailable information. This work presents a fuzzy linear programming approach based on the possibility theory. It applies this approach to solve multi-product and multi-time period MDPD problems with imprecise goals and forecast demand by considering the time value of money of related operating cost categories. The proposed approach attempts to minimize the total manufacturing and distribution costs by considering the levels of inventory, subcontracting and backordering, the available machine capacity and labor levels at each source, forecast demand and available warehouse space at each destination. This study utilizes an industrial case study to demonstrate the feasibility of applying the proposed approach to practical MDPD problems. The primary contribution of this paper is a fuzzy mathematical programming methodology for solving the MDPD integration problems in uncertain environments.     

基于差分蜂群算法的电力系统经济负荷分配

针对电力系统经济负荷分配问题,提出一种有效的差分蜂群算法．受差分进化算法的启发,该算法基于差分进化操作改进了雇佣蜂的搜索方式,提高了探索能力和收敛速度．此外,提出一种有效的修复机制以保证新个体的可行性．该算法在带有阀点效应和多燃料特征的典型电力系统经济负荷分配问题上进行了测试．仿真结果验证了所提算法的有效性．     

蒙特卡罗法及其在射弹散布仿真中的应用

作战仿真的真实性需要对抗双方火力射击效果的真实体现。文中提出了一种利用蒙特卡罗法进行射弹散布仿真的方法 ,并将结果与实际情况进行了比较。该方法已用于装甲兵数字化作战仿真实验室的作战仿真中     

BP神经网络在剩余油分布预测中的应用研究

我国多数油田经过一次、二次采油后,仅能采出地下总储量的30%左右,这意味着有60%～70%的剩余石油仍然残留在地下成为剩余油。加强剩余油分布规律研究、提高石油采收率不仅有着可观的经济效应,而且关系到国家石油战略的安全。本研究应用神经网络的原理,基于BP网络使用MATLAB语言建立一个剩余油分布的预测系统。该系统通过学习在地理坐标和孔隙度之间建立一个非线性函数关系,以此来预测任何区域的孔隙度,再通过孔隙度与剩余油饱和度之间的关系达到剩余油分布预测的目的。