潮汐河网可降解有机物降解系数研究

潮汐河网具有其独特的水物理及水化学特性。本文采用珠江三角洲河网区域20个水样的BOD降解实验数据,并用BOD反应一级动力学方程进行数据拟合,结果表明,潮汐河网水体BOD降解过程的延滞期消失,远离污染源河段河水的BOD降解过程两阶段区分不明显,降解过程符合BOD反应一级动力学方程。此外,潮汐河网河水的降解系数随时间的变化过程是随机的。      

BP及RBF人工神经元网络对臭氧生物活性炭水处理系统建模的比较

运用BP和RBF人工神经元网络建立臭氧生物活性炭系统模型,考察了两个网络对水处理系统建模的适应性。研究表明,BP和RBF人工神经元网络的臭氧生物活性炭系统模型准确地描述了系统影响因素的关系,可以求出系统中臭氧的经济投量;用BP人工神经元网络建立水处理系统模型,泛化能力好,但逼近速度较慢;运用RBF人工神经元网络建模,泛化能力较差,但逼近速度快。该项研究克服了运用传统方法建模的不足,为实现水处理系统的优化设计提供了可行的途径。     

Reliability evaluation of fire alarm systems using dynamic Bayesian networks and fuzzy fault tree analysis

In almost all industries, fire alarm systems play a vital role in the reducing the risks associated with fires and damages. Therefore, it is necessary to evaluate their reliability and performance in emergency situations. The present study aimed to use fault tree analysis (FTA) to determine the root causes involved in the failure of fire alarm systems, to use Fuzzy set theory and expert elicitation to determine relative probabilities, and finally, to evaluate the reliability of a fire alarm system using dynamic Bayesian networks (BNs) during a thirty-six months period. A total of 29 basic events were detected from the FT. The reliability of the fire alarm system was estimated at 0.954 according to the FT and 0.957 according to conventional BNs. The reliability of the fire alarm system after 36 months was estimated at 0.375 according to dynamic BNs. All the events involved in the failure of fire alarm systems were drawn in the fault tree diagram. The results indicate that remodeling of these systems and simultaneous construction activities are the most important factors in the failure of the fire alarm system. System reliability can also be increased to 0.965 by providing preventive and control measures to reduce the probability of critical events.     

Audience perceptions of high-status ties and network advantage: The market for coaching jobs in the National Collegiate Athletic Association (2000–2011)

Social ties with high-status others can be a potent signal of an individual's underlying quality and future promise. Individuals in competitive markets, therefore, have an incentive to publicly claim connections to high-status others. However, cognitive limitations and biases can make social network connections difficult for observers to reliably discern, and claims to high-status ties can go unrecognized by the audience. Our core contention is that claims to high-status affiliation are advantageous only when the audience recognizes the claim—unrecognized claims, like unreliable signals, do not deliver advantage and can backfire. Further, we draw on the literature on imprinting and develop arguments for why some people are more likely to make claims to high-status ties and why some claims to high-status ties are more likely than others to be recognized by the audience. We test our arguments with data from the market for head coaching jobs in NCAA basketball (2000–2011). Our study contributes to the sparse literature on how social network ties that exist in the minds of third-party observers influence individual attainment in market settings; and it offers new insights into how imprinting processes shape the perception and use of high-status network ties.     

基于人工神经网络的街道峡谷NO_x浓度的数值模型研究

通过对反向传播人工神经网络的算法和网络结构的研究,发现拟牛顿算法训练速度较快,能够较好地接近误差目标值,同时建立了包括输入层、隐含层、输出层的人工神经网络三层拓扑结构。通过对街道峡谷人工神经网络的训练,模拟计算了街道峡谷NOx浓度分布值。结果显示,训练误差和测试误差比为1.11,训练样本的模拟值与实测值的相关系数为0.93,测试样本的模拟值与实测值的相关系数为0.87,模拟值与实测值的相关系数均高于显著水平为α=0.05与α=0.01所对应检验性表的相关系数临界值。该模型能够用于街道峡谷污染物浓度的模拟计算,具有较好的泛化能力。     

国外工程教育(本科)专业认证分析与借鉴

介绍国际相互承认的协议——《华盛顿协议》(WA);分析美国、德国和英国等国家工程教育(本科)专业认证机构的特点、准则和程序;揭示各国发展教育路径不同,环境与条件各异,体现的以行业为背景、以行业专家为核心的理念。同时介绍我国工程教育(本科)专业认证试点工作的状况、工作程序、通用标准和专业标准;分析工程教育(本科)专业认证的基本内涵;明确工程教育(本科)专业认证标准是指导工程教育(本科)专业发展的准绳。笔者认为,该专业认证标准对维护工程教育(本科)专业认证的权威性、保证工程教育(本科)质量、促进工程专业人才的流动有至关重要的作用。     

Toward Integrative Management Advice of Water Quality, Oil Spills, and Fishery in the Gulf of Finland: A Bayesian Approach

Understanding and managing ecosystems affected by several anthropogenic stressors require methods that enable analyzing the joint effects of different factors in one framework. Further, as scientific knowledge about natural systems is loaded with uncertainty, it is essential that analyses are based on a probabilistic approach. We describe in this article about building a Bayesian decision model, which includes three stressors present in the Gulf of Finland. The outcome of the integrative model is a set of probability distributions for future nutrient concentrations, herring stock biomass, and achieving the water quality targets set by HELCOM Baltic Sea Action Plan. These distributions can then be used to derive the probability of reaching the management targets for each alternative combination of management actions.     

基于指标规范值的室内空气客观评价的概率神经网络模型

为了建立简单、普适、通用的概率神经网络的室内空气评价模型,在适当设定室内空气各项指标的参照值及指标值的规范变换式基础上,使室内空气同级标准不同指标的规范值差异尽可能小,从而用规范值表示的各指标都可用同一个规范指标"等效"替代。因此,概率神经网络隐层各类模式的基函数中心矢量的各指标分量值与同级标准所有15项指标规范值的均值等同。将基于指标规范值的概率神经网络模型用于室内空气的评价实例进行检验,验证了该模型的普适性、通用性和简便性。     

安全工程专业人才培养模式与专业知识结构优化

阐述了构建高校安全工程专业人才培养新模式应遵循的原则,从安全工程专业人才市场所需的知识结构出发,以安全专业学科科学理论作指导,对高校安全工程专业的知识结构进行优化,提出了其课程体系设置方案,并应用于安全工程专业人才培养的实践教学.     

人工神经网络在深圳市水库富营养化评价中的应用

对富营养化评价标准进行插值获取大量的样本,建立了基于BP人工神经网络的富营养化评价模型。将模型应用于评价深圳市13座主要水库的富营养化状况,对其成因进行分析,并提出了对策与建议。研究结果表明,石岩水库与深圳水库为轻度富营养化,占评价水库总数的15.4%;西丽水库等11座水库为中营养,占评价水库总数的84.6%。人工神经网络用于建立湖库富营养评价模型是适合的。