基于神经网络的闸阀模糊可靠度计算

为提高闸阀可靠度计算准确性,将模糊准则引入闸阀可靠性设计,将闸阀应力与阀体通径、内压之间隐式关系显式化,并基于神经网络构建地震工况下闸阀数学模型;利用蒙特卡洛法,计算闸阀在常规方法下的可靠度;利用正态型隶属函数描述闸阀强度的模糊性,计算闸阀在考虑模糊强度时的可靠度;对比强度的模糊性对可靠度计算结果的影响,分析不同隶属函...     

A transportation network assessment tool for hazardous material cargo routing: Weighing exposure health risks,proximity to vulnerable areas,delay costs and trucking expenses

The inherent risks associated with accidental releases of hazardous materials during transport have drawn attention and concerns in the recent decades. The aim of this study is to propose a tool for evaluation and comparison of the transportation networks which can be used to assess the routing options between origins and destinations of the cargos for their suitability for transporting hazardous material cargos by tanker trucks and to identify routes which provide lower accidental release risks, lower public exposure risks, and offer economical benefits. Each route segment of transportation networks were evaluated using specific criteria which included health risk and cost of delay in case of an accidental release of materials, trucking cost and proximity to vulnerable areas. Since, the health impact of hazardous materials differ depending on the characteristics of the material being transported as well as release quantities and atmospheric conditions; this paper aimed in providing a tool that can be used to estimate the impact radius (for health risks) after accidental release of hazardous materials by taking into account different atmospheric conditions based on the meteorological data and solar elevation angle. The Gaussian air dispersion model paired with ArcGIS using Python programming were employed to estimate the health risk impact zones by considering the meteorological data, and accordingly to analyze road segments for cost impacts (delay and trucking costs), and the proximity to vulnerable areas. The route assessment tool was demonstrated with a case study. The results of this study can efficiently aid decision makers for transportation of hazardous materials.     

基于BP神经网络的上市公司CEO报酬实证研究

近年来的研究表明,CEO报酬不仅受公司业绩的影响,还受到其他诸多因素的影响,而且,CEO报酬与其决定因素之间往往存在着非线性关系。本文以2003-2005年沪深股市的A股上市公司为样本,采用BP神经网络对CEO总报酬、CEO年薪、CEO持股价值及其决定因素分别进行训练和学习,结果表明：（1）网络训练输出值与实际值的拟合度分别达到91.09%、97.23%和78.44%;（2）网络的预测能力相对于传统的线性回归模型分别提高了92.72%、92.08%和53.89%。因此,本文认为在分析和确定CEO报酬水平时引入神经网络模型是可行的。     

逆转录-聚合酶链反应(RT-PCR)技术同时检测水中多种肠道病毒

建立了一种利用通用引物RT-PCR技术检测水中肠道病毒的方法.利用脊髓灰质炎病毒1～3型,柯萨奇病毒B3型作为参考病毒株,根据肠道病毒RNA5′非编码区中具有高度同源性的序列来设计通用引物.比较了M-MLV酶和AMV酶的逆转录效果,AMV酶能够成功地从地表水和生活污水中逆转录病毒RNA,更适于实际应用.对比研究了PCR过程中的退火温度,c(Mg2＋)等因素对RT-PCR检测结果的影响,选择退火温度55　℃,c(Mg2＋)为2　mmol/L的反应条件,优化了RT-PCR检测方法.通过检测水样中接种的连续稀释的病毒,确定了该检测方法的灵敏度为38　CCID₅₀.考察人工污染的地表水、污水、二级处理出水样品发现,检测灵敏度基本一致.该方法可应用在实际环境的肠道病毒检测中.      

Survivor needs or logistical convenience? Factors shaping decisions to deliver relief to earthquake‐affected communities,Pakistan 2005–06

In Bureaucratizing the Good Samaritan , Waters (2001) argues that bureaucratic rationality distracts humanitarian agencies from the needs of the people they are supposed to assist, in favour of other values that their institutional frameworks dictate. We test his claim by investigating the response to the Pakistan 2005 earthquake. One of us (Dittemore) worked with the United Nations Joint Logistics Centre in the theatre, managing a relief cargo shipment database. The response, known as 'Operation Winter Race', was hampered by extreme logistical challenges, but ultimately succeeded in averting a second disaster resulting from cold and starvation. We use statistical models to probe whether survivor needs significantly guided decisions to deliver relief to affected communities. Needs assessments remained incomplete and incoherent. We measure needs through proxy indicators and integrate them, on a Geographic Information System (GIS) platform, with logistics and relief delivery data. We find that, despite strong logistics effects, needs orientations were significant. However, the strength of decision factors varies between commodity types (food versus clothing and shelter versus reconstruction materials) as well as over the different phases of the response. This study confirms Thomas's observation that logistics databases are rich 'repositories of data that can be analyzed to provide post-event learning' (Thomas, 2003, p. 4). This article is an invitation for others to engage in creative humanitarian data management.     

粮食基础设施震后恢复重建关键问题研究

在对汶川8.0级地震后绵阳市粮食基础设施破坏情况调研的基础上,提出恢复与发展并重、粮食基础设施节点与网络并行、推进行业整合和信息化的建设思路,规划了绵阳市灾后恢复重建的维修保障和重建发展项目,并对规划实施效果进行了经济和社会效益分析。     

Two-echelon closed-loop supply chain deterministic inventory models in a batch production environment

This paper considers a two-echelon closed-loop supply chain consisting of a manufacturer and a remanufacturer at the upper echelon and a retailer at the lower echelon. The retailer faces a constant demand from customers, which is satisfied through recovered and new products received from the remanufacturer and the manufacturer, respectively. The manufacturer produces the product with finite rate, whereas the recovery of returned product is instantaneous at the remanufacturer. We develop three models to determine the optimal production-inventory policy of the players for minimizing the joint total cost of the system. In the first model, the retailer receives the product in batches from the manufacturer and the remanufacture simultaneously, whereas in the second and third models, the batches are received alternatively. In the third model, however, the procurement of raw material at the manufacturer is also considered. Numerical illustration is presented to examine the impact of certain key parameters.     

反渗透处理稀土氨氮废水试验研究

根据稀土冶炼厂排放的碳铵沉淀洗涤废水的水质情况,采用NH4Cl和 NaCl模拟废水进行了反渗透可行性对比实验。模拟实验发现,在相同条件下反渗透对NaCl 较NH₄Cl 有着更高的去除率,而NH₄Cl 相对NaCl则有着更高的产水速率。实际废水试验结果表明,在恒定操作压力范围内回收率为65%的条件下,NH₄Cl浓度为2.85 g/L的碳铵沉淀洗涤废水经反渗透处理其NH₄Cl去除率为77.3%,可作为氨氮废水的预处理。对该废水处理成本进行了分析,得出其约为2.7元/m³,比相近浓度氨氮废水的氨吹脱处理成本节省约26%。     

人工神经网络方法在拟建小区域环境质量评价中的应用

人工神经网络的评价方法用于小区域环境质量评价中,根据本地区特点因地制宜地选择环境质量参数,代入模型中进行环境质量评价及预测,对用于环境质量评价的BP人工神经网络模型进行了改进,即对网络模型的训练样本进行了扩充,从而提高了模型的抗干扰能力和准确性.将改进了的BP人工神经网络模型应用于四川省资阳市沱江二桥拟建项目小区域的大气、地表水环境质量评价中, 对该市小区域大气、地表水环境质量状况进行评价,评价结果表明,BP人工神经网络模型用于环境质量评价是可行的,且评价结论客观,评价模型普遍适用.     

基于模糊神经网络的机动车驾驶教练员职业适宜性研究

提出应用模糊神经网络系统,建构教练员职业适宜性的3个要素(即心理素质、驾驶技能和知识的表达阐述能力)的学习样本,分析"三要素"的8项特征参数指标——场依存性、速度估计能力、交通安全意识、简单反应、选择反应、跟踪能力、行车注意力、表达阐述能力等,使用K-均值法对实验样本进行初始分类,形成标准学习样本,使用该样本对所构建系统进行训练和调试。利用经调试训练后的系统,依据所测教练员的心理、心理参数对其职业适宜性进行评价。试验表明:建立的教练员职业适宜性仿真模型能取得很好的评价效果。