A Bayesian network-based approach for the assessment and management of ageing in major hazard establishments

Currently, there is an increasing attention towards ageing of industrial equipment, as the phenomenon has been recognised as a cause of severe accidents, recorded in the last years in many process establishments. Recent studies described ageing through a number of key-factors affecting the phenomenon by accelerating or slowing it down. The Italian Competent Authority for the prevention of chemical accidents (Seveso III Directive) adopted a short-cut method, accounting for the assessment of these factors, to evaluate the adequateness of ageing management during inspections at Seveso sites. In this paper, a Bayesian Network was developed, by using the data gathered during the first application of the short-cut method, with the aim to verify the robustness of the approach for ageing assessment and the validity of the a priori assumptions used in assessing the key-factors. The structure of the Bayesian network was established by using experts’ knowledge, whereas the Counting Learning algorithm was adopted to execute the parameter learning by means of the software Netica. The results showed that this network could effectively explore the complex logical and uncertain relationships amongst factors affecting equipment ageing. Results of the present study were exploited to improve the short-cut method.     

基于VB6.0的供水管网震害预测方法和软件

为了提高供水管网震害预测的效率,修订了现有供水管网震害预测模型,应用Visual Basic 6.0软件平台,开发了供水管网震害预测软件。震害预测软件提供了两方面的预测功能,分别为不同地震烈度下供水管段基于三态的破坏等级预测和供水管网基于五态的破坏等级预测。软件实现了批量供水管段及整个管网的震害预测,且可以进行管网在设定地震下的震害预测,提高了预测效率。经算例分析,验证了软件的可靠性。     

面向实时人群动力学分析的深度基本图网络

当前行人疏散实验中基本图计算方法通常是通过对每个行人进行跟踪实现的.但这种跟踪方法难以实现实时人群动力学分析.针对这一问题,提出了深度基本图网络.实验提出的网络框架由两个模块组成,即多尺度递归卷积神经网络(MSR-Net)和光流模块,分别对行人密度和行人速度进行估计.具体来讲,MSR-Net学习了输入图像与行人密度图之...     

基于CA的城市形态扩展多解模拟——以北京市东部平原区情景分析为例

构建了一个基于人工神经网络的约束型城市扩展CA模型。利用该模型,预测了北京市东部平原区在3种情景规划之下的未来50年的城市形态,为不同的城市发展模式之间的比较分析奠定基础。然后以2024年的北京东部平原区模拟城市形态为基准,从自然生态功效、社会服务功效、经济利益功效3个方面对3种规划模式进行了情景分析,从而系统的比较了3种规划模式的复合生态功效,为城市规划决策提供有力的支持。     

我国汽车报废回收利用体系框架初探

主要介绍了国内外废旧汽车回收处理现状,并从法制建设、回收网络构建、回收技术研究、宣传教育等方面提出了我国应对废旧汽车回收利用的对策建议。     

小波网络在大气污染物浓度预测中的应用

提出一种“分解-重构-预测”小波网络的大气污染物浓度的预测方法。通过小波分解,把浓度序列分解为不同频段的小波系数序列,再对各层的小波系数子序列重构到原尺度上,然后对小波系数序列采用相匹配的BP神经网络模型进行预测,最后合成浓度序列的最终预测结果。经对二氧化硫浓度预测证明,该方法预测模型推广能力强,预测精度高。     

BP神经网络在台风路径预报中的应用

利用前馈型BP神经网络模型,对发生于中国沿海的热带气旋的移动路径进行了预报应用研究.根据中国<台风年鉴>发布的每个台风过程记录,对预报试验的台风个例分别选取了经度、纬度、中心气压和最大风速等81个因子,由多元回归选取了其中相关性好的因子,进行网络的学习训练,在获取前24h间隔6h的4次台风信息的基础上,用来预报了台风未来24h,48h和72h的短期路径变化.将该方法预报结果与CLIPER模式预报结果进行了比较,结果表明,BP神经网络模式的预报精度比CLIPER模式的高.     

汶川地震在江苏的强震动记录及地震影响场

2008年5月12日四川汶川发生M8.0大地震,江苏数字强震动台网固定观测台站、宿迁和溧阳断层观测存放台阵共获取该次地震有效强震动事件45个,计134条加速度记录。本文介绍了这些强震动记录分析处理的基本情况及其时域与频域的一些特点;编写SICalculate谱烈度计算程序和D2InterP二维插值程序,输入所获取的汶川地震26组实测强震动记录数据,得到该次地震在江苏地区的峰值加速度与谱烈度的等值线图,并就区域内地震影响场特征进行了初步研究。     

Anaerobic tapered fluidized bed reactor for starch wastewater treatment and modeling using multilayer perceptron neural network

Anaerobic treatability of synthetic sago wastewater was investigated in a laboratory anaerobic tapered fluidized bed reactor(ATFBR) with a mesoporous granular activated carbon(GAC)as a support material.The experimental protocol was defined to examine the effect of the maximum organic loading rate(OLR),hydraulic retention time(HRT),the efficiency of the reactor and to report on its steady- state performance.The reactor was subjected to a steady-state operation over a range of OLR up to 85.44 kg COD/(m~3.d).The COD removal efficiency was found to be 92% in the reactor while the biogas produced in the digester reached 25.38 m~3/(m~3·d) of the reactor. With the increase of OLR from 83.7 kg COD/(m~3.d),the COD removal efficiency decreased.Also an artificial neural network(ANN) model using multilayer perceptron(MLP)has been developed for a system of two input variable and five output dependent variables. For the training of the input-output data,the experimental values obtained have been used.The output parameters predicted have been found to be much closer to the corresponding experimental ones and the model was validated for 30% of the untrained data.The mean square error(MSE)was found to be only 0.0146.     

河流综合水质评价方法比较研究

为探讨综合水质评价结论的科学合理性,对典型的7种河流综合水质评价方法,包括单因子评价法、污染指数法、模糊评价法、灰色系统评价法、层次分析法、人工神经网络法、水质标识指数法,在归类分析其特性的基础上,针对代表性的评价样本,进行了综合水质评价比较研究。主要结论为：①单因子评价法以最差水质指标所属类别作为综合水质类别,评价结论表现为过保护;②污染指数法能够直观判断综合水质是否达到功能区目标,但是不能判断综合水质类别;③对模糊数学法、灰色系统评价法、层次分析法、BP人工神经网络法和水质标识指数法等5种典型评价方法,当综合水质为Ⅰ~Ⅴ类水情形时,这几种方法评价结论基本一致,证明这5种典型评价方法对Ⅰ~Ⅴ类水的评价结论具有科学合理性;④当综合水质为劣Ⅴ类水时,模糊数学法、灰色系统评价法、层次分析法、BP人工神经网络法的评价结论偏保守,而水质标识指数法解决了劣Ⅴ类水质的连续性描述问题,能够对劣Ⅴ类水进行科学合理评价,并对Ⅰ~Ⅴ类水、劣Ⅴ类水不黑臭、劣Ⅴ类水黑臭进行全面、科学合理的定性与定量评价.