Improving traceability in continuous processes using flow simulations

Traceability is normally difficult to achieve in continuous processes, since there are no natural batch structures. In this article, we demonstrate flow-based simulation using process data to improve traceability in a continuous pelletising process. Using the simulation model, the engineers could test the impacts of process disturbances, identify cause and effect relations and aid control in case of process disturbances. In a field trial where the chemistry of an additive was varied during production of a special product, the simulation forecasts predicted the level of the chemical content after the plant within the errors that the engineers found acceptable.     

Simulation of the p-generalized Gaussian distribution

In this paper, we introduce the p-generalized polar methods for the simulation of the p-generalized Gaussian distribution. On the basis of geometric measure representations, the well-known Box–Muller method and the Marsaglia–Bray rejecting polar method for the simulation of the Gaussian distribution are generalized to simulate the p-generalized Gaussian distribution, which fits much more flexibly to data than the Gaussian distribution and has already been applied in various fields of modern sciences. To prove the correctness of the p-generalized polar methods, we give stochastic representations, and to demonstrate their adequacy, we perform a comparison of six simulation techniques w.r.t. the goodness of fit and the complexity. The competing methods include adapted general methods and another special method. Furthermore, we prove stochastic representations for all the adapted methods.     

Simulation of Balakrishnan skew-normal order statistics

ABSTRACT

The novel Balakrishnan skew-normal distribution introduced in 2008 has received considerable interest. Here, we derive stochastic representations for simulating order statistics of the novel Balakrishnan skew-normal distribution. The resulting algorithms are more efficient than the ordinary sorting algorithm.     

The Times They are A’changing: Multigenerational Family Simulations

Multigenerational households are increasingly affecting both the individual and family as well as community organizations and social policies. Social work and other family studies students can profit from educational modalities that use adult learning applications through a systems life-course perspective, the whole family aging over time. Family simulation software—addressing multigenerational families, such as two or more adult generations living together—builds on a previous paper (Marriage & Family Review, Feb. 2015). Social class, among other demographic and environmental variables, is emphasized. Agent-based family social network simulation of multigenerational families can facilitate experiential learning. An automatically generated life events report, based on both factual data and specific family characteristics, can be used as a classroom case study for role playing and assessing.     

模糊车辆路径问题的一种混合遗传算法

在对模糊车辆路径问题进行简单描述的基础上,通过引入决策者主观偏好值的概念,给出了解决该问题的基本思路,建立了具有模糊特征的车辆路径问题的模糊机会规划模型,提出了求解该问题的一种基于模糊模拟的混合遗传算法。同时,在最小化总行驶距离的目标下,通过随机模拟方法研究了决策者主观偏好值的选择对最终决策目标的影响作用,并给出了其最佳取值范围。     

大型医院血液库存系统订货点决策的仿真研究

血液是一种典型的易变质物品。本文以国内某大型医院的血液库存系统为对象,依照其运作流程,基于该系统运行的历史数据建立了一个离散事件系统仿真模型对这一系统进行研究,得到了该系统的最优订货点。本文的研究有助于血液库存管理措施的制定与改进,对其它易变质物品库存系统的管理也有一定的借鉴作用。     

internet网上旱地农业土壤灌溉和需水管理决策支持系统

本文通过对因特网旱地农业土壤灌溉和需水管理决策支持的设计和分析的介绍,较具体地阐明了internet技术在旱地农业土壤灌溉研究的应用,讲述了系统所提供的各种功能,深入浅出地阐明了该系统提供的决策分析模型。说明该系统是旱地水资源可持续利用的重要辅助决策工具。     

基于遗传算法的概率准则组合证券模拟求解

针对概率准则意义下的组合证券投资模型,采用随机模拟技术和遗传算法相结合的思 想, 设计出求解算法, 并用Matlab 语言实现. 求解算法适用于证券收益率服从任意分布的情 况, 甚至不考虑证券收益率分布, 用实际数据进行模拟和优化. 实例证明, 该算法有很好的 收敛性及较高的计算效率.     

证券市场流动性与交易者群体变动的混沌研究

从证券市场微观结构角度,利用交易者群体可变的动态模型,分别在确定与不确定性金 融环境下,研究离散交易状态下市场的形成过程,并分析了交易者群体变动的混沌条件. 结果 表明,市场流动性的最低标准是买卖双方的交易者群体要有一个恰当的比例,市场达到稳定流 动性的时间与描述离开股市交易者的参数有关,通过交易制度对交易者群体参数的影响,可实 现对市场过程的控制,最后给出仿真计算.