溢油应急决策中的设备优化调度方法研究

针对溢油应急,溢油应急设备库及其设备配置的特点,以溢油处理开始时间最早和调度的设备库数量最少为目标,在满足第一个目标的设备库集合中,分别采用穷举方法和贪心方法求取满足第二个目标的最优解。穷举方法保证能够获得最优解,但是计算复杂;贪心方法计算简单,适用于溢油应急设备的配置特点。用算例验证了该方法的有效性和高效性。     

长江感潮河段溢油风险评价体系构建及应用

长江感潮河段水动力条件复杂,对该水域溢油事故缺少相应的风险评价指标体系。为科学评价长江感潮河段溢油风险,从溢油事故对上游水体、敏感点、敏感区影响 3 个要素出发,构建风险评价指标体系,包括危害区特征、危害期特征共 23 个指标。应用该指标体系,基于 EFDC 二维水动力-油粒子模型,以长江南京段水域某码头溢油事故为研究对象,开展溢油风险评价,模拟计算涨急、落急、涨憩、落憩 4 种典型事故发生工况下的风险评价指标值。结果表明;事故发生在落急或涨憩时刻时不会对上游水域产生影响,发生在落憩时刻时对事故点上游水域影响距离最远,发生在落急时刻时将最快影响到下游的敏感点和敏感区,持续时间与水动力特性密切相关。建立的评价指标体系可以较为全面地刻画溢油风险影响特征,为长江感潮河段溢油风险评价提供量化指标和评价工具。     

基于形态仿生的海上溢油回收装置设计与评估

为解决海上溢油回收装置功能与形态单一的问题,提出一种自下而上的设计程序构建仿生设计方法。由综摄法求取生物特征意象集合以确定仿生目标集;结合哈里斯图表对目标集进行筛选以确定仿生原型;利用生物简化优化法分析仿生原型的结构特征关系,将结构特征与形态分析求得的设计要素进行耦合得到初步仿生造型设计方案;运用模糊数学中模糊集的概念对设计方案进行优先级排序;对择优方案进行模态分析,验证方案是否符合结构动力学要求,从而建立具有系统指导意义的仿生设计方法。利用方法指导设计,得到功能与形态间满足设计需求且高耦合度的蝠鲼仿生溢油回收装置。将该方法模型应用于产品仿生设计中,可以为海上应用类产品设计提供有效的理论指导,提高海洋技术类产品整体水平。     

异构网络管理系统间分布式协作机制*

从全局全网出发对通信业务进行提供和保障,要求作为支撑体系中的网络管理系统之间能够动态协作。而分布式协作方式相对于集中式协作方式具有性能和可扩展性等方面的优势。分析了网络管理系统对分布式协作的需求,在一个基于Web services的动态协作网络管理体系结构的基础上,将网络管理系统间的协作转换为由网络管理系统提供的管理服务之间的协作,定义了异构网络管理系统之间的分布式协作机制,设计并实现了一个原型系统来验证该分布式协作机制。     

A forecasting solution to the oil spill problem based on a hybrid intelligent system

Oil spills represent one of the most destructive environmental disasters. Predicting the possibility of finding oil slicks in a certain area after an oil spill can be critical in reducing environmental risks. The system presented here uses the Case-Based Reasoning (CBR) methodology to forecast the presence or absence of oil slicks in certain open sea areas after an oil spill. CBR is a computational methodology designed to generate solutions to certain problems by analysing previous solutions given to previously solved problems. The proposed CBR system includes a novel network for data classification and retrieval. This type of network, which is constructed by using an algorithm to summarize the results of an ensemble of Self-Organizing Maps, is explained and analysed in the present study. The Weighted Voting Superposition (WeVoS) algorithm mainly aims to achieve the best topographically ordered representation of a dataset in the map. This study shows how the proposed system, called WeVoS-CBR, uses information such as salinity, temperature, pressure, number and area of the slicks, obtained from various satellites to accurately predict the presence of oil slicks in the north-west of the Galician coast, using historical data.     

Evaluating the application of research-based guidance to the design of an emergency preparedness leaflet

Guidelines for the design of emergency communications were derived from primary research and interrogation of the literature. The guidelines were used to re-design a nuclear emergency preparedness leaflet routinely distributed to households in the local area. Pre-test measures of memory for, and self-reported understanding of, nuclear safety information were collected. The findings revealed high levels of non-receipt of the leaflet, and among those who did receive it, memory for safety advice was poor. Subjective evaluations of the trial leaflet suggested that it was preferred and judged easier to understand than the original. Objective measures of memory for the two leaflets were also recorded, once after the study period, and again one week or four weeks later. Memory for the advice was better, at all time periods, when participants studied the trial leaflet. The findings showcase evaluation of emergency preparedness literature and suggest that extant research findings can be applied to the design of communications to improve memory and understandability.     

应用BP神经网络预测油页岩含油率

根据测井资料计算油页岩含油率多采用△logR法或改进的△logR法,这些方法中参数获取过程中易产生诸多误差,且这些方法是建立在油页岩含油率与特征测井曲线值是线性关系的基础上的,而在实际非均质性地层中,测井对油页岩含油率参数的响应在本质上必然是非线性的。基于此,运用BP神经网络来预测柴达木盆地北部地区侏罗纪油页岩含油率。首先分析研究区段测井数据的数理统计分布特征,在优选学习样本的基础上再采用一种基于LM（ Levenberg-Marquardt）算法的BP神经网络进行含油率预测,最后得出一组由40个连接权值与11个阈值组成的含油率参数解释模型,油页岩含油率预测值与岩心实验室分析值吻合很好,均方误差能控制在0.1918。因此,运用此模型可以预测相同地质背景条件下的油页岩含油率。     

Coping with blackouts: A practice theory approach to household preparedness

The article focuses on how rural households cope with blackouts caused by winter storms. We approach household preparedness using a practice theory perspective, and argue that preparedness is mundanely preformed as part of everyday practices. The data material consists of at home visits to 14 households from Norway and Sweden. The results demonstrate that households cope with blackouts by activating and mobilising competences, meanings and materials belonging to different practices, and that this is an ongoing process to ensure the continuation of everyday life during disruption. The article concludes by arguing for the need to bring forward studies on informal preparedness activities, in a research field where household preparedness tends to be framed using a top‐down perspective on crisis management.     

基于粒子群优化算法的神经网络在油品质量预测中的应用

粒子群优化算法是基于群体智能的全局优化技术,它通过了粒子间的相互作用,对解空间进行智能搜索,从而发现最优解。其优势在于操作简单,容易实现。文中将粒子群算法和神经网络进行融合,优化神经网络的权值和域值,充分发挥了粒子群算法的全局寻优能力和BP算法的局部搜索优势,并与改进的BP算法进行了比较 。油品质量预测的实例表明,将粒子群算法用于神经网络的优化,收敛速度更快,预测精度更高,而且算法简单。     

Variations in employees' perceptions of organizational disaster preparedness

Few studies have sought to understand the different kinds of preparedness measures public, private and nonprofit organizations adopt and the factors motivating these organizations to adopt different kinds of preparedness measures. The present study addresses these gaps in research using perceptions from 1,960 public, private and nonprofit employees. Results indicate significant variations in public, private and nonprofit employees' perceptions of the kinds of preparedness measures their organizations adopt. Findings also suggest there are variations in the factors motivating public, private and nonprofit organizations to adopt different kinds of preparedness measures. The results provide important insights to emergency managers aiming to increase the levels of disaster preparedness among organizations within their communities.     

BP神经网络用于预测多参数关联变压器油的性能

基于变压器油性能参数之间的关联性,采用BP神经网络方法,在Matlab平台下研究预测多参数关联变压器油的性能,利用变压器油日常的监测数据,建立击穿电压与4个影响因素的关联模型.论文分别就常规BP算法和变学习速率、变动量因子的改进BP算法进行了比较研究,结果表明,改进BP算法模型的预测结果精度较高,预测值与实际值的相对误差在5%左右.本方法可以为变压器故障的早期诊断、预测防范和及时处理提供科学依据,具有重要的实际应用价值.     

Project preparedness and the emergence of implementation problems in ERP projects

The problems that organizations face in implementing an enterprise-wide ERP project are linked to their level of understanding of what is involved in such an endeavor and how it influences their initial preparations. We sought to demonstrate empirically the causal relationship between the organization's preparedness and the emergence of implementation problems. We examined four case studies to extract insight into the criticality of certain factors and the type of problems created when no moderating measures were taken by project managers. Consequently, we developed a predictor-outcome model mapping a lack of preparedness with implementation problems.     

Revisions of the ADIOS oil spill model

For several years, the National Oceanic and Atmospheric Administration Hazardous Materials Response Division (NOAA/HAZMAT) has been using and distributing the computer software package called ADIOS™ (Automated Data Inquiry for Oil Spills) to aid responders in oil spill cleanup. ADIOS forecasts the weathering processes and characteristics of oil slicks. Based on new research results and analysis since the first version was released, a major update revises and improves previous algorithms, plus adds new modules for other weathering processes and for spill cleanup strategies. The weathering processes included in the new version, called ADIOS2, are spreading, evaporation, dispersion, sedimentation, and emulsification. The user cleanup options are dispersants, in-situ burning, and skimming. Different types of release scenarios can be simulated and the user is allowed to enter ranges for selected input variables with the resulting uncertainty displayed in the model output.     

INDU网络对于战场动态协同的支持

为了在多维战场上赢得胜利．我军必须做到诸作战单元之间的精确协同。本文分析了战场上动态协同的各种情况，描述了战斗动作间的时态依赖和逻辑依赖，介绍了区间代数的扩展—INDU网络，并利用它来支持战场上的动态协同。     

基于主动网络技术的网络管理

本文主要介绍了主动网络技术的网络管理原理以及主动网络的几种执行体制,并描述了主动网络的基本工作过程。     

基于神经网络建模和遗传算法的重油脱盐系统优化研究

概述了重油脱盐系统的BP神经网络建模以及基于遗传算法的系统优化过程，将遗传算法与惩罚函数法相结合应用于约束优化的问题，改善了遗传算法的局限性。同时为了将不等式约束优化问题转化为单目标优化问题，对惩罚函数法进行了改进。结果表明：此方法可以有效解决静电脱盐问题。     

网络管理模式浅析

通过对现存的各种网络管理模式进行分析和对比，指出其各自的缺点和长处，从而能使用户根据不同的网络规模和网络特点选择适合自己的网络管理模式来建立自己的网络管理系统，还提出一种适合现在网络特点的网络管理模式。     

无线传感器网络的网络管理框架研究与设计

无线传感器网络的网络管理是个崭新的研究领域,目前的研究或与应用结合紧密,或与具体功能密切相关,通用的管理框架较少。深入分析了无线传感器网络管理的内容,应包含并扩展ISO定义的功能域,增加了对能量管理、在线编程管理和路由管理的支持。详细介绍了一种通用管理框架的设计思路,包括节点代理和网络功能结构设计,为无线传感器网络网络管理系统的实现奠定了基础。     

基于TD-LTE的石油信息化专网解决方案研究

目前,我国工业领域获得了空前繁荣发展尤为迅速,石油需求量大大增加,而解决石油问题便成为当务之急.本文首先概述了石油专网的发展现状与1TD-LTE原理,然后从TD-LTE专网建设方案和专网方案优势两方面阐述了TD-LTE石油专网方案,最后论述了石油企业专网建设应用,并对全文进行总结.     

A software system for assessing the spatially distributed ecological risk posed by oil shipping

A maritime accident involving an oil tanker may lead to large scale mortality or reductions in populations of coastal species due to oil. The ecological value at stake is the biota on the coast, which are neither uniformly nor randomly distributed. We used an existing oil spill simulation model, an observation database of threatened species, and a valuation method and developed a software system for assessing the spatially distributed ecological risk posed by oil shipping. The approach links a tanker accident model to a set of oil spill simulations and further to a spatial ecological value data set. The tanker accident model is a Bayesian network and thus we present a case of using a Bayesian network in geographic analysis. A case in the Gulf of Finland is used for illustration of the methodology. The method requires and builds on an extensive data collection and generation effort and modeling. The main difference of our work to earlier works on using a Bayesian network in geospatial setting is that in our case the Bayesian network was used to compute the probabilities of spatial scenarios directly in a global sense while in earlier works Bayesian networks have been used for each location separately to obtain global results. The result was a software system that was used by a distributed research team.