基于数据挖掘的复杂装备维修辅助决策研究

文章通过某装备维修信息框架分析,维修数据预处理,然后以维修记录为例,挖掘出了维修件之间关联规则,并采用决策树分类方法对维修件进行了分类,这些规则和分类结果可以为维修计划制定、器材采购、视情维修等方面提供决策依据。     

基于检索决策树的螨种分类鉴定专家系统

应用传统的分类检索方法进行粉螨亚目螨种的分类鉴定是一个复杂、繁琐的过程。随着人工智能技术的发展,采用专家系统技术编制螨种分类鉴定软件将改变传统的分类鉴定方式。通过学习粉螨亚目的分类学和专家系统的相关知识,将螨种的分类鉴定与专家系统有机地结合起来,采用面向对象方法,设计并实现了基于决策树的螨种分类鉴定专家系统。通过构建基于面向对象的决策树知识表示模型,提炼出螨种知识库的记录结构,根据节点对象的逻辑关系,设计了基于决策树的推理机制,并按照一定的推理控制策略实现了螨种的分类鉴定。结果证明,满足了用户的需要,具有重要的实践价值。     

基于组播源移动的组播树修改过程研究

特定源组播(SSM)是现在应用最广泛的组播模型。随着无线网络的快速发展,移动用户不断增加,移动环境为越来越多的用户提供有限的、共享的带宽,这样的现实更加重了网络对组播服务的需要。然而,特定源组播(SSM)对组播源移动的支持仍然是一个有待解决的问题。本文将针对组播树修改协议(TM)进行分析和改进,进一步完善组播树修改协议过程。     

Monoterpene concentrations in fresh,senescent, and decaying foliage of singleleaf pinyon (Pinus monophylla Torr. & Frem.: Pinaceae) from the western Great Basin

Senescent foliage from pines is potentially a large contributor to the total monoterpene content of the litter layer, and the availability of these compounds as phytotoxins may result from release of these compounds into the vapor phase. In order to determine the fate of several monoterpene hydrocarbons in the natural environment, we examined their concentrations in fresh, senescent, and decaying needles from 32 single-leaf pinyon pine (Pinus monophylla Torr. & Frem.: Pinaceae) trees growing at two different locations. Total monoterpene content was highest in the fresh needles (mean=5.6 ± 2.2 mg/g extracted air dry weight), but also remained relatively high in senescent needles (mean=3.6 ±1.8 mg/g extracted air dry weight), either still attached to the tree or forming the freshest layer of understory litter. Decaying needles within a dark decomposing layer of litter material 5–20 cm from the surface were found to contain much lower amounts of total monoterpenes (average: =0.12 ±0.06 mg/g extracted air dry weight). Further investigation of the fate of these compounds in the pinyon understory is required to determine if these hydrocarbons are indeed exerting phytotoxic characteristics.     

Event-driven,pattern-based methodology for cost-effective development of standardized personal health devices

Experiences applying standards in personal health devices (PHDs) show an inherent trade-off between interoperability and costs (in terms of processing load and development time). Therefore, reducing hardware and software costs as well as time-to-market is crucial for standards adoption. The ISO/IEEE11073 PHD family of standards (also referred to as X73PHD) provides interoperable communication between PHDs and aggregators. Nevertheless, the responsibility of achieving inexpensive implementations of X73PHD in limited resource microcontrollers falls directly on the developer. Hence, the authors previously presented a methodology based on patterns to implement X73-compliant PHDs into devices with low-voltage low-power constraints. That version was based on multitasking, which required additional features and resources. This paper therefore presents an event-driven evolution of the patterns-based methodology for cost-effective development of standardized PHDs. The results of comparing between the two versions showed that the mean values of decrease in memory consumption and cycles of latency are 11.59% and 45.95%, respectively. In addition, several enhancements in terms of cost-effectiveness and development time can be derived from the new version of the methodology. Therefore, the new approach could help in producing cost-effective X73-compliant PHDs, which in turn could foster the adoption of standards.     

前向树状紧急疏散网络的自适应性控制策略分析

针对前向树状的紧急疏散网络,提出了一种不需要进行需求预测且具有适应性和强鲁棒性的分散式控制疏散策略.通过分析如何确定典型匝道与快速路交汇点处的最优疏散路线,明确了构建可控疏散网络的基本原则.定义了前向树状紧急疏散网络,并对所构建网络的适用范围和具体风险水平标定处理作了明确说明.针对前向树状网络的典型子结构,给出了可以始终充分利用下游通行能力,且充分考虑上游来流具有较高风险水平特点的具体疏散路线选择及放流策略.在上述典型子结构分析基础上,给出了包括如何逆流向确定路段限制性通行能力、顺流向确定路段最大可行流量以及实时动态调整疏散策略等基本步骤的网络疏散策略.最后,通过一个数值算例,比较了新策略与纯粹上游优先策略、纯粹下游优先策略的运行效率,证明了新的适应控制策略的可行性与有效性.     

基于不确定决策树分类算法在滑坡危险性预测的应用

滑坡灾害预测受多种因素影响,其中降雨等不确定因素存在难以获取数据及有效处理等难题,为提高滑坡危险性预测的准确率,根据滑坡灾害发生相关理论及决策树分类原理,提出了基于不确定决策树算法在滑坡危险性预测的方法.该方法引入不确定因子降雨,并将不确定因子和其余评价因子一起,根据不确定决策树算法理论构建出不确定决策树,建立滑坡危险性等级预测模型,并用延安市宝塔区的实例进行验证.实验结果表明,该预测方法取得了较高的总体精度和有效精度,达到了滑坡预测的精度标准,且两项预测精度均高于传统C4.5决策树方法.     

基于多决策树的RFID入侵检测模型

为了能够有效对RFID系统的已知攻击和未知攻击进行检测和预警,在分析大量RFID安全协议的基础上,提出了利用构建多决策树的方法对RFID系统的入侵行为进行检测。通过分析,得到所构造出的多决策树能够发现针对RFID系统的攻击之间的关系,并且具有可扩展性和高效性,使之能够适用于各种实际的RFID系统的应用。     

近红外分析网络共享平台中复杂工作流实现算法

近红外分析共享平台中的采集工作流是一个以数据为中心的工作流。对系统中复杂采集工作流的跳转执行过程进行了详细分析,针对自由工作流跳转造成的数据和状态不一致性的问题,提出了一个任务执行优先关系算法,计算采集工作流中各个活动任务执行次序关系值,并构造一个执行次序关系树,记录各任务活动的状态信息;在流程回退、撤销、跳转时保证了数据和状态的一致性,较好地实现了跨任务活动的跳转。应用结果表明,此算法能够正确高效地实现复杂流程的跳转。     

基于先验知识的自适应多叉树防碰撞算法

为提高无线射频识别(RFID)系统快速识别大量标签的能力,提出一种基于先验知识的自适应多叉树防碰撞算法。利用标签访问的规律性和标签分布的随机性,在不同的搜索深度,根据已有的先验知识和碰撞比特信息估计待识别的标签数量,从而动态地自适应选择搜索叉树。通过有效减少碰撞和空闲时隙数,大幅提高读写器搜索和识别标签的能力。理论分析与仿真实验结果表明,该算法能克服传统自适应多叉树防碰撞算法的缺点,合理选择初始搜索叉树,尤其在待识别标签数量较多的场合,可有效提高RFID系统的吞吐率。