Fault-tree analysis for liquefied natural gas terminal emergency shutdown system

Natural gas, one of the cleanest, most efficient and useful of all energy sources, is a vital component of the world’s supply of energy. To make natural gas more convenient for storage and transportation, it is refined and condensed into a liquid called liquefied natural gas (LNG). In a LNG site, safety is a long-team and critical issue. The emergency shutdown (ESD) system in the LNG receiving terminal is used to automatically stop the pumps and isolate the leakage section. Fault-tree analysis (FTA) has been widely used for providing logical functional relationships among subsystems and components of a system and identifying the root causes of the undesired failures in a system. In the conventional FTA for the ESD system, we usually assume that exact failure probabilities of events are collected. However, in most real applications, first, the FTA for the ESD system needs to be made at a early design or manufacturing stage, certain new components normally used without failure data; secondly, sometimes the environmental change in the system during the operation periods. This makes more difficult to gather past exact failures data for the FTA. To complete the FTA of the ESD system under these uncertain situations, we apply the intuitionistic fuzzy sets (IFS) theory to the FTA. We generate the intuitionistic fuzzy fault-tree interval, and the intuitionistic fuzzy reliability interval for the ESD system. We also present an algorithm to find the critical components in the system based on IFS–FTA and determine weak paths in the ESD system, where the key improvement must be made.     

Should we try to measure software quality attributes directly?

Most external software quality attributes are conceptually subjective. For example, maintainability is an external software quality attribute, and it is subjective because interpersonally agreed definitions for the attribute include the phrase ‘the ease with which maintenance tasks can be performed’. Subjectivity clearly makes measurement of the attributes and validation of prediction systems for the attributes problematic. In fact, in spite of the definitions, few statistically valid attempts at determining the predictive capability of prediction systems for external quality attributes have been published. When validations have been attempted, one approach used is to ask experts to indicate if the values provided by the prediction system informally agree with the experts’ intuition. These attempts are undertaken without determining, independently of the prediction system, whether the experts are capable of direct consistent measurement of the attribute. Hence, a statistically valid and unbiased estimate of the predictive capability of the prediction system cannot be obtained (because the experts’ measurement process is not independent of the prediction system’s values). In this paper, it is argued that the problem of subjective measurement of quality attributes should not be ignored if quality is to be introduced into software in a controlled way. Further, it is argued that direct measurement of quality attributes should be encouraged and that in fact such measurement can be quantified to establish consistency using an existing approach. However, the approach needs to be made more accessible to promote its use. In so doing, it would be possible to decide whether consistent independent estimates of the true values of software quality attributes can be assigned and prediction systems for quality attributes developed.

用于求解约束优化问题的自适应佳点集进化算法

提出一种用于求解约束优化问题的自适应佳点集进化算法.新算法利用佳点集原理设计多点交叉算子,该交叉算子能够根据父代个体的相似度自适应调整交叉点的位置和子代个体的数目,产生具有代表性的子代个体.在约束处理技术上,改进了Deb的三条比较准则,提出一种新的适应度函数用于比较个体优、劣的比较准则.通过对13个标准测试函数的试验比较验证了新算法的有效性和稳健性.     

构造基于证据理论的群组信任管理模型

针对资源共享系统中节点的恶意行为,提出一种基于证据理论的群组信任管理模型,在节点间服务与被服务的过程中建立信任关系,抑止恶意节点的破坏行为.首先根据改进的直方图法计算节点直接信任值,利用改进的冲突信任加权证据组合规则计算推荐信任值;然后融合本地信任值和其它节点推荐信任值完成对目标节点的最终信任评估;最后进一步通过服务节点选择算法选择可信度较高的节点作为服务提供节点,避免服务请求节点得到错误或破坏性的资源.通过仿真实验对此模型在对抗恶意攻击时的有效性进行了验证.     

基于蚁群算法的攻击图分析

分析攻击图分析中求解攻击图最小关键集的方法和作用。在研究蚁群算法的基础上,将其引入对攻击图的最小关键集的求解中,对Cincotti等人提出的针对权值最小碰集问题的蚁群算法进行改进,并用实验验证了算法的可行性。     

不一致信息系统的粗糙集快速约简算法

针对以依赖性作为属性重要性度量的约简算法效率较低、不能有效处理不一致信息系统的问题,提出一种时间复杂度为O（｜A｜2｜U｜）、基于错误分类率（ER）的快速约简算法。根据等价类计算的包含关系和正区域与属性个数的单调关系,采用ER作为属性重要性的度量。在UCI数据集合上测试该算法,结果证明了其有效性。     

P2P环境下的蠕虫检测算法

P2P下载与网络蠕虫具有相似的搜索机制,导致网络蠕虫难以被检测并定位。该文提出一种融合危险理论和ID3分类算法的检测算法D—ID3。利用熵理论分析P2P应用、蠕虫、正常主机的属性特征,得到轴属性。利用ID3分类算法得到可以区分蠕虫、P2P和正常流量的分类规则。实验结果表明,该算法能成功检测出网络蠕虫,其误警率较低。     

基于可拓神经网络的火灾探测算法

为解决传统单一传感器式的火灾探测器容易造成火灾报警的漏报和误报的问题,采用多传感器信息融合技术,将温度、烟雾浓度和CO浓度等多个参数相结合,进行综合分析,对火灾进行早期预测。采用可拓神经网络作为数据融合算法,以温度、烟雾浓度、CO气体浓度三个物理参量作为输入,以三种火灾预警等级作为输出。通过仿真分析结果表明：火灾正确识别率很高,达到93.9%以上。同时通过与传统BP神经网络的对比,表明可拓神经网络在数据融合的速度和可靠性上有突出的优势,从而使可拓神经网络实际应用于火灾早期预测成为可能。     

SEBCDS:无线传感网络的连通支配集算法

由于无线传感网络(WSN,sireless sensor network)节点受到能量和传输距离的约束,有效地构建连通支配集(CDS,connected dominating set)是提高WSN数据传输效率的重要技术手段.然而,现存的多数构建CDS算法只强调CDS规模,没有考虑网络的能量均衡.为此,提出了基于休眠机制和能量均衡的连通支配集(SEBCDS,sleep-and energy-balance-based connected dominating set)算法.SEBCDS算法首先选择剩余能量高和邻居节点多的节点作为支配节点,并为支配节点选择副支配节点,然后采用休眠机制,让一部分支配节点工作,另一部分支配节点休眠,降低网络能量消耗.仿真结果表明,提出的SEB-CDS算法能够降低能量消耗、延长CDS的生命周期.与TCDS算法相比,能量消耗降低了23％,CDS的生命周期提高了约31%.     

基于模糊理论的井下配电网防越级跳闸保护算法

针对目前煤矿井下漏电保护时常出现保护准确性不高,继电装置拒动、误动甚至引起越级跳闸造成较大范围停电的情况,选择基于暂态分量的小波分析法、基于稳态分量的零序电流幅值比较法、零序电流相位比较法等几种保护方法,利用模糊理论对这几种保护结果进行多判据信息融合处理,以提高保护的准确性和可靠性.依据这些保护算法来分析所建立的仿真模型,证实了基于模糊理论的多判据保护算法能有效地实现井下故障定位,减少了拒动、误动,并以此降低了越级跳闸的可能.