人群组织关系中的势位法则

片面地和局部地追求个人英雄主义的单极效应,已不是当今社会发展的方向和终极目标,更好地实现具有组织关系的人群最大效应策略将自觉或不自觉地成为了亘古不变的真理,因此人群整体效应的最优化势位法则的提出有其现实紧迫性和现实导向性。本文提出了以“势”作为描述人群组织关系的基本概念及对于不同人群组织关系中的势描述准则,并形成了人群组织关系的最优化势位法则。无论是大系统还是小系统的人群组织关系,这种势位法则都可用于实现该系统整体效应的全面提升。在信息和计算技术飞速发展的将来,这种势位法则对未来社会可能有着更加重要的影响和意义。     

面向服务的复杂成形装备产品架构设计与优化

复杂成形装备作为高端制造产业的基础装备,是各产业转型升级和技术进步的重要保障。同时快速发展的互联网与大数据等新兴信息技术已经成为装备制造业创新不可或缺的组成部分,极其深刻地影响着复杂成形装备产业的制造模式、发展战略以及产品的开发方式。本文研究了面向服务的复杂成形装备产品架构设计与优化方法。采用公理化设计的域结构思想,建立需求域、功能域和架构域之间的映射关系;提出了基于QFD的功能生成方法以及功能模型约简方法;利用DMM建立产品架构和服务架构之间的关联关系;利用模块化理论方法,并考虑成本因素对产品架构进行优化。     

信息不对称下价格随机的应急数量折扣契约研究

以市场需求和市场价格随机波动的二级供应链为研究对象,寻找其在信息不对称条件下绩效优化的路径。通过显示原理分别构建生产成本和销售成本信息不对称时应急供应链的数量折扣契约模型,得到最优订货量与最佳批发价策略。通过具体的算例加以验证,分析了信息不对称程度对供应链上成员及整个供应链绩效的影响。研究结果表明：当突发事件造成市场价格随机波动和市场需求变化时,供应链上的跟随者能从隐瞒私人信息中获利。但当市场需求增大时,整个供应链绩效受损,反之则反是。这与以往研究在市场需求随机、市场价格固定和信息不对称条件下的结论迥异。     

震后伤员救援车辆两阶段规划模型及算法研究

不确定情景下的应急物资配送和车辆路径优化问题是目前国内研究的一大热点,其中 震后伤员运送车辆调度及路径优化问题随着近几年地震等自然灾害的频繁发生也逐渐引起人 们的重视． 本文采用聚合优化算法对灾区进行应急救援区域划分,建立了以总救援时间最短和 相对综合救援权重值最大为目标的救援车辆两阶段数学规划模型,设计了带三角函数变异的 离散型萤火虫优化算法进行求解,并与常规算法求解结果做了对比分析． 通过算例进行模拟实 验表明,所提出的模型和算法可以有效解决地震情景下的伤员救援车辆调度问题,且改进算法 的全局搜索性能更优．     

What does Brunei teach us about using Human Development Index rankings as a policy tool?

The Bruneian Government has set an ambitious target to achieve a top 10 ranking on the United Nations Development Programme's (UNDP) Human Development Index (HDI) by 2035. To achieve its objective (described in a national strategy document called the Wawasan 2035), Brunei's economy needs to grow by 6% to 7%. Is setting an HDI target a good way to govern Brunei's policy‐making? Is it a good way to govern any country's policy‐making? In this article, we look at the role of HDI‐rank targets in economic and fiscal policy. We show that such a headline target (much like a profit target in a private company) automatically sets targets for growth in various economic sectors and fiscal policy targets. As such, HDI‐rank targeting may provide a useful mechanism for co‐ordinating development policies and for monitoring progress against a wide range of development goals using only one number.     

湖南省高等教育结构优化对策研究——基于区域产业结构调整的视角

区域产业结构与劳动力就业结构具有相关性.因此培养人才的高等教育必须根据产业结构调整趋势进行自身结构上的优化.湖南省高等教育结构优化包括:合理配置综合性大学、多科性大学、单科性院校的类型结构优化,适度发展研究生教育、本科生教育和专科教育的层次结构优化,省会中心城市与其他各市州协调发展的区域结构优化,学科专业改造与发展同时并举的科类结构优化.完善非正规高等教育体系的形式结构优化,来源多元化的投资结构优化.     

试论产业集群经济背景下江西职业教育结构的优化

产业集群经济逐渐成为区域经济的主体。职业教育结构合理与否,直接影响着产业集群经济的建立与发展。本文探析了优化江西职业教育结构与服务江西产业集群经济发展的问题。     

An intuitive risk factors search algorithm: usage of the Bayesian network technique in personalized medicine

The article focuses on the application of the Bayesian networks (BN) technique to problems of personalized medicine. The simple (intuitive) algorithm of BN optimization with respect to the number of nodes using naive network topology is developed. This algorithm allows to increase the BN prediction quality and to identify the most important variables of the network. The parallel program implementing the algorithm has demonstrated good scalability with an increase in the computational cores number, and it can be applied to the large patients database containing thousands of variables. This program is applied for the prediction for the unfavorable outcome of coronary artery disease (CAD) for patients who survived the acute coronary syndrome (ACS). As a result, the quality of the predictions of the investigated networks was significantly improved and the most important risk factors were detected. The significance of the tumor necrosis factor-alpha gene polymorphism for the prediction of the unfavorable outcome of CAD for patients survived after ACS was revealed for the first time.     

Particle swarm optimization based Liu-type estimator

In this study, a new method for the estimation of the shrinkage and biasing parameters of Liu-type estimator is proposed. Because k is kept constant and d is optimized in Liu’s method, a (k, d) pair is not guaranteed to be the optimal point in terms of the mean square error of the parameters. The optimum (k, d) pair that minimizes the mean square error, which is a function of the parameters k and d, should be estimated through a simultaneous optimization process rather than through a two-stage process. In this study, by utilizing a different objective function, the parameters k and d are optimized simultaneously with the particle swarm optimization technique.     

Modified genetic algorithm-based clustering for probability density functions

This article modifies two internal validity measures and applies them to evaluate the quality of clustering for probability density functions (pdfs). Based on these measures, we propose a new modified genetic algorithm called GA-CDF to establish the suitable clusters for pdfs. The proposed algorithm is tested by four numerical examples including two synthetic data sets and two real data sets. These examples illustrate the superiority of proposed algorithm over some existing algorithms in evaluating the internal or external validity measures. It demonstrates the feasibility and applicability of the GA-CDF for practical problems in data mining.