任务分配与调度中遗传算子的设计

应用遗传算法等进化方法进行任务分配与调度为越来越多的计算机学者们所关注。基于任务排列的知识表示 ,常规的标准遗传操作算子并不总是有效的。好的遗传算子对算法收敛性及收敛到好点是非常重要的。在列表编码的知识表示基础上 ,设计了三个有针对性的遗传算子 ,即改进的交配算子、内部交配算子和一种作为变异的迁移算子。模拟实验结果与分析表明这些算子对任务分配与调度是有效的。     

基于多子网语言决策图的空管体系绩效评估

为评估空管体系综合绩效水平,制定了关键绩效领域和指标,提出基于多子网语言决策图的群体评估模型。采用多子网策略分析领域及指标间的影响关系,应用语言尺度辅助群体专家建立了领域及指标间的初始判断矩阵和影响连接矩阵。给出了模型的求解方法,在求得各子网内准则的全局权重后,聚合即可得到体系的综合评估值。案例分析表明,相比于不考虑领域及指标间影响的情况,模型结果能更客观、全面地展示各领域及指标的权重,更显著地揭示空管体系间的差距。     

基于合作博弈的智能集群自主聚集研究

智能集群是指由大量智能体构成、采用自组织策略协作完成任务的群体。以无人车集群系统协同监视再入体着靶过程为任务背景,开展智能集群自组织策略的关键技术研究。设计了无人车集群执行再入体着靶协同监视的集群行为模式,提出了基于合作博弈的智能集群自组织策略,各智能体以实现群体聚集为“合作目标”,以降低自身能量消耗为“竞争目标”,开展博弈,基于微粒群算法规划局部路径,最终使群体系统涌现出聚集行为。仿真实验验证了设计的自主聚集策略的有效性。     

Business and peace in the Niger Delta: what we know and what we need to know

The global restructuring of state–society relationships driven by neoliberal logic has not only allowed for the taming of the ‘state’, which has paradoxically accentuated its inadequacies, but has also facilitated, for better or for worse, the emergence of business – especially transnational corporations – as a major political force in global governance. Consequently, while the issues of peace and conflict have traditionally been the concern of governments, businesses are now increasingly being expected to make peace and conflict their concern. However, despite claims and counterclaims that businesses can be moneymakers and peacemakers, analyses of the relationship between business and peace remain largely embryonic. This paper seeks to contribute to this emerging business and peace debate by drawing on insights from the Niger Delta conflict to ascertain what we know and what we need to know if businesses are to become peacemakers in conflict zones in Africa.     

防空导弹制导系统一体化仿真系统框架

介绍了一种采用现代先进仿真技术思想、支持面向对象的建模与仿真、用于防空导弹全弹道飞行动态仿真的一体化仿真系统框架 ,详细说明了它的主要特点、构成及各部分的功能     

用于动平衡测试的MDAC窄带跟踪滤波器

为了从强干扰噪声中提取出与转速同频的振动分量,且适应转速波动时的情形,利用互相关原理导出了跟踪滤波方法,并采用乘法数模转换器(MDAC)设计并实现了窄带跟踪滤波器。实验结果表明,其增益相对误差优于0.2%,相位绝对误差优于0.4°,当转速变化率不超过9000r/min2时,滤波器的输出能够跟踪转速的变化。该滤波器能较好地满足动平衡测试的需要。     

Information theory for ranking and selection

We study the classical ranking and selection problem, where the ultimate goal is to find the unknown best alternative in terms of the probability of correct selection or expected opportunity cost. However, this paper adopts an alternative sampling approach to achieve this goal, where sampling decisions are made with the objective of maximizing information about the unknown best alternative, or equivalently, minimizing its Shannon entropy. This adaptive learning is formulated via a Bayesian stochastic dynamic programming problem, by which several properties of the learning problem are presented, including the monotonicity of the optimal value function in an information-seeking setting. Since the state space of the stochastic dynamic program is unbounded in the Gaussian setting, a one-step look-ahead approach is used to develop a policy. The proposed policy seeks to maximize the one-step information gain about the unknown best alternative, and therefore, it is called information gradient (IG). It is also proved that the IG policy is consistent, that is, as the sampling budget grows to infinity, the IG policy finds the true best alternative almost surely. Later, a computationally efficient estimate of the proposed policy, called approximated information gradient (AIG), is introduced and in the numerical experiments its performance is tested against recent benchmarks alongside several sensitivity analyses. Results show that AIG performs competitively against other algorithms from the literature.     

构建军民融合法治保障体系的几点理论思考

法治是推动军民融合发展的重要基石,不管从整合主体力量、优化资源配置,还是保障各系统有效运行等方面都发挥着不可替代的作用。针对当前军民融合法治保障体系存在的法规制度"碎片化"、滞后性,以及适用性不强等矛盾问题,军民融合法治保障体系的构建必须把握好坚持党的领导与维护法治的权威性,坚持改革创新与维护法治的稳定性,坚持分工协作与维护法治的系统性,坚持开放共融与维护法治的独特性等基本原则。     

分布式数据库系统中数据一致性维护方法研究

分布式数据库系统是数据库领域中的一个主要研究方向 ,数据一致性维护是分布式数据库系统中的一个非常关键的技术问题。在深入分析和比较各种维护数据一致性方法的基础上 ,提出了一种较为有效的维护数据一致性的方法 ,详细论述了该方法如何解决并发执行引起的冲突问题 ,以及如何利用消息队列机制保持各数据副本的一致     

自动阈值选取与边缘检测相结合的图像分割算法

提出了一种自动阈值选取与边缘检测相结合的阈值分割算法 ,试验表明该算法能够避免过分割现象 ,具有良好的分割效果