以可靠性为中心的水轮机组检修模式研究

以可靠性为中心(RCM)的维修模式是在一般视情维修的基础上,吸收以可靠性为中心的维修分析法的优点,充分考虑到经济性、可靠性原则,并与先进的设备诊断技术相结合的一种维修模式。介绍了水轮机组RCM维修模式,重点分析了根据经济性和可靠性原则分别确定隐患检测间隔期,以及用威布尔分布拟合机组零部件故障间隔时间分布的表示及参数的获得。     

关于斜插式基础受力的分析探讨

为优化线路的整体投资,需在线路设计各个环节进行控制,包括路径的优化、铁塔及基础的选型等,其中基础型式的选择对工程投资影响极大,文章对斜插式基础受力问题做简要分析.     

军队医院网络信息系统的安全分析

随着网络技术在医院的应用,其安全性日益受到重视。首先结合军队医院信息系统网络应用的特点,从硬件系统、软件系统、环境因素、人为因素等方面分析该网络系统的安全性;最后研究该网络系统安全可能造成的威胁,并提出安全应对措施。     

基于渐进约束违背删除策略的服务合成执行路径优化

在面向服务计算领域,服务合成正成为分布异构资源整合、业务集成的一个新型计算模式。在开放互联的因特网环境下,由于存在多个功能相似但服务质量不同的服务提供商,从而导致一个抽象的服务合成方案存在多条可执行路径。然而,在满足用户综合QoS约束需求的情况下,如何有效协同单个服务的QoS从多条候选路径选出一条优化的执行路径,便成为服务合成QoS研究中的一个关键问题。遗憾的是,该问题还没有得到很好的解决。为此,我们提出一个采取渐进约束违背删除策略建立优化执行路径的方法。我们的方法能够避免探测多条执行路径,而是在靠本地最优化策略建立的执行路径上,通过全局QoS计算和QoS约束检查模型找出QoS约束违背,并进而采取渐进约束违背删除策略逐渐删除这些约束违规,并建立起一条近优的执行路径。实验表明,我们的方法很好地降低了建立优化执行路径的时间复杂性。     

BPEL流程监视的可视化实现

When a BPEL process is executed, it is necessary to dynamically monitor the process. BPEL is a executable language, which is not suitable for visual monitoring. On the other hand, BPMN is designed to visually describe business process and is more intuitive for monitoring. To visually monitor a BPEL process, transformation from BPEL to BPMN is necessary. However, current study of transformation from BPEL to BPMN does not support the transformation of "link" activity. Besides, no work has been done to add supplementary information into BPMN during transformation. In this paper, we transform nested BPEL process into a flat BPMN process graph without hierarchy through applying a flattening strategy. Especially, we analyze various scenarios of the transformation of link activity, and provide a method to deal with it. Besides, we analyze the mapping between BPEL activities and BPMN graph, through which we found out that some supplementary information cannot automatically obtained from BPEL process. These supplementary information need to be added during transformation. At the end of this paper, we present the structure of our monitoring tool which is based on our transformation algorithm.     

多数据项广播调度策略

多数据项广播是移动计算环境中一种重要的数据访问方式.为减少用户的平均访问时间和响应最多事务请求,提出了一种新的多数据项广播调度策略.调度策略分为两个阶段,第一阶段根据各事务包含的数据项数目和对重复申请数据项的处理选择事务请求;第二阶段对已选择的事务请求用QEM算法进行调度.实验结果表明,它比现有的QEM算法有更高事务调度成功率和更短的平均访问时间.     

一种特征加权FCM算法的图像重建技术研究

针对传统FCM(Fuzzy C-means)算法中初始聚类中心选取的随机性以及对初始值敏感的问题,提出一种基于进化策略的色彩空间加权的FCM聚类算法.通过在RGB(Red Green Blue)色彩空间矢量中设置加权矩阵来补偿各色彩的非均匀性,并采用一种类内最小距离最大的统计聚类算法来初始化聚类中心.实验结果表明,该算法能有效减少颜色量化后的均方差值,保持重建图像的整体层次和局部特征细节,对研究图像处理技术有较强的实际意义.

Abstract：

Aiming at a defect on randomness of the initial clustering center choosing and sensitivity of initial value in tradition FCM(fuzzy C-means) algorithm, a clustering algorithm about FCM of weighted color space based on evolutionary strategy is proposed. By interposing weighted matrix in RGB(Red Green Blue) color space, the color's inhomogeneous is compensated. And by using a statistics clustering algorithm of minimal maximal distance, clustering center is initiated. The experimental results show that the algorithm can decrease effectively the mean square deviation of color quantization, keep overall arrangement of ideas and part characteristic detail in image reconstruction, and has practical value to the study of the image process technology.     

基于模糊理论的非处方药的满意度评价系统

为了帮助顾客从众多对症的非处方药中选出最满意的药品,提出了开发1个基于Web的非处方药满意度评价系统。系统根据顾客提供的典型症状,采用疾病与症状相结合的选药策略,查找出所有对症的非处方药,并以药品安全性、疗效、稳定性、易用性、价格作为评价因素,根据顾客的关注角度和关注程度确定各因素权重,用模型b=W·R对对症药品进行满意度评价,按满意度高低依次推荐。经实际应用,系统推荐准确度在70%以上。     

面向多层次知识表达的贝叶斯分类模型研究

提出多模式贝叶斯分类算法,由变量值之间的条件独立和条件相关性推断因果关系,根据每个完整随机样本而非整个样本空间构造子模式.结合局部计算近似推理进行概率密度和条件概率分布估计,在此基础上采用后离散化策略自动确定连续变量边界.在UCI机器学习数据集上的实验结果证明了该算法的合理性和有效性.     

Auto-tuning strategy for evolutionary algorithms: balancing between exploration and exploitation

Genetic Algorithms (GAs) and other Evolutionary Algorithms (EAs), as powerful and broadly applicable stochastic search and optimization techniques have been successfully applied in the area of management science, operations research and industrial engineering. In the past few years, researchers gave lots of great idea for improvement of evolutionary algorithms, which include population initialization, individual selection, evolution, parameter setting, hybrid approach with conventional heuristics etc. However, though lots of different versions of evolutionary computations have been created, all of them have turned most of its attention to the development of search abilities of approaches. In this paper, for improving the search ability, we focus on how to take a balance between exploration and exploitation of the search space. It is also very difficult to solve problem, because the balance between exploration and exploitation is depending on the characteristic of different problems. The balance also should be changed dynamically depend on the status of evolution process. Purpose of this paper is the design of an effective approach which it can correspond to most optimization problems. In this paper, we propose an auto-tuning strategy by using fuzzy logic control. The main idea is adaptively regulation for taking the balance among the stochastic search and local search probabilities based on the change of the average fitness of parents and offspring which is occurred at each generation. In addition, numerical analyses of different type optimization problems show that the proposed approach has higher search capability that improve quality of solution and enhanced rate of convergence.