基于复杂网络的城市燃气输配系统失效因素分析

将复杂网络相关理论方法引入城市燃气输配系统失效因素的分析中。选取引起城市燃气输配系统失效的主要影响因素为节点,以它们之间的相互关系为边,建立网络并进行相关分析。发现节点的度分布近似具有幂律的特性,幂指数为1.76;通过节点度的分析,确定出管道附属设备、用户设施失效、第三方影响破坏等因素为引起输配系统失效的主要原因,与引起燃气事故的统计分析资料基本相符合。这为确定城市燃气输配系统关键失效因素提供了一种新的思路。     

矿井通风网络数据可靠性检验

进行矿井通风阻力测定时,由于受环境的温度、湿度、压力传递存在时间差以及测点处标高不准确等因素的影响,根据实测数据,计算所得矿井巷道基础数据存在一定的误差,常用的测量数据检验方法只能对若干条通路进行闭合回路检验,而不能对全矿井通风网络基础参数进行可靠性检验。本文中所介绍的检验方法将风网基础数据输入通风网络解算软件,以实测风量和经过计算所得巷道风阻为基准,实测风量为目标条件,进行计算机通风网络模拟,对全矿井巷道风阻进行连续的优化调整,使通风网络模拟结果与实际测定各巷道风量基本符合,从而实现全矿井风网基础数据的可靠性检验。该方法在某矿进行了实际应用,实践证明此方法科学、准确的获得了全矿巷道风阻参数,为矿井的通风改造奠定了技术基础。     

基于ANN的土壤重金属分布和污染评价研究

农田土壤重金属污染与备受关注的农产品安全问题有密切联系,因此对其进行研究意义重大。以江苏省南通市为研究区,利用采样点实测数据,借助神经网络模型(ANN)并结合3S技术对问题进行研究,从而对土壤重金属的空间动态分布进行描述,并对各个空间位点重金属的污染状况进行评价。结果表明,神经网络模型能够智能地学习各个样点的空间位置与该点各重金属含量之间的映射关系和预先设计好的分类评价模式,并能够稳健地对各个空间插值点处的重金属含量和各个位点的重金属污染状况进行预测和评价。结论显示,南通市大部分农田土壤重金属污染较轻,但也存在局部地区的严重污染。结论与实际情况相符,表明神经网络模型可以为农田土壤重金属的研究提供一个新的思路和方法。     

Exploration of spatial morphometry and socioeconomic variables in modelling urban land use change

The incorporation of land use (LU) data with socioeconomic data is a main issue in modelling. This is as a result of difference in data model and scale. This study proposed and tested the change–pattern approach, which allows the incorporation of these data sets in modelling LU change. Focusing on LU dynamics for a selected part of the Thames Gateway within the City of London, the approach tested two different methods of input selection for the modelling operations. Variables selected from these two methods serve as inputs into several neural networks tested in order to identify the direction of change for each of the LU types within the study area. The result shows that direction of LU change across the study area could be identified when spatial morphology of the area and socioeconomic variables are considered. Some classes of change could be identified fairly accurately using landscape metrics indicating level of fragmentation, extent of LU patches, shape complexity of LU patches in combination with some socioeconomic variables.     

Simulation-based fault propagation analysis—Application on hydrogen production plant

Recently production of hydrogen from water through the Cu–Cl thermochemical cycle is developed as a new technology. The main advantages of this technology over existing ones are higher efficiency, lower costs, lower environmental impact and reduced greenhouse gas emissions. Considering these advantages, the usage of this technology in new industries such as nuclear and oil is increasingly developed. Due to hazards involved in hydrogen production, design and implementation of hydrogen plants require provisions for safety, reliability and risk assessment. However, very little research is done from safety point of view. This paper introduces fault semantic network (FSN) as a novel method for fault diagnosis and fault propagation analysis by using evolutionary techniques like genetic programming (GP) and neural networks (NN), to uncover process variables’ interactions. The effectiveness, feasibility and robustness of the proposed method are demonstrated on simulated data obtained from the simulation of hydrogen production process in Aspen HYSYS^®. The proposed method has successfully achieved reasonable detection and prediction of non-linear interaction patterns among process variables.     

基于GA-ELM浆体管道输送临界流速预测模型研究

针对浆体管道输送临界流速预测难度大、精确度低等技术难题,提出了基于极限学习机(ELM)的临界流速预测模型,用训练集对模型进行训练,以验证集预测值的均方误差作为适应度函数,利用遗传算法(GA)对ELM模型参数进行优化,应用优化得到的ELM模型对预测集进行预测。以某矿山为例,模型参数优化结果如下:隐含层节点数L为400,输入权值ai、偏置向量bi最优组合下预测结果适应度为0.0201。采用优化的ELM模型对预测集进行预测,预测结果的最大相对误差x=3.96%,平均相对误差y=1.58%,对比BP神经网络(x=12.95%)和SVM模型(x=3.19%),表明ELM模型更加精确、高效。     

Environmental Protection Bureau Leadership at the Provincial Level in China: Examining Diverging Career Backgrounds and Appointment Patterns

This paper analyses the career backgrounds of local government officials in provincial Environmental Protection Bureaus (EPBs) in China and explains the appointment patterns of Chinese EPB bureaucrats. Using biographical information of provincial EPB heads and drawing on fieldwork conducted in Shanxi Province and Inner Mongolia, this paper finds that only one-fourth of the provincial EPB heads were promoted through the bureau ranks within the EPBs, while the remaining three-fourths were appointed from positions outside the environment field. Further, nearly all EPB heads' professional backgrounds and associated networks can be clearly categorized as environmental, business, provincial government, or local government oriented. This paper delineates these four types of Chinese EPB leaders and explains why an awareness of the different professional orientations is critical to understanding environmental regulation and protection in China. These findings have implications for inferring the unique characteristics of a province's EPB leadership, the implementation capacities of provincial EPBs, and the appointment preferences of provincial leaders.     

Efficient energy management strategies for hybrid electric vehicles using shuffled frog-leaping algorithm

This paper proposes two novel approaches for the problem of energy management in hybrid electric vehicles. Shuffled frog-leaping algorithm (SFLA) is a recently proposed population-based optimization algorithm. This paper first formulates energy management as an optimization problem and optimizes the problem using SFLA. Then the paper makes use of SFLA as a training algorithm to train artificial neural network (ANN) and this SFLA-trained ANN is used for energy management. Interestingly, the proposed approaches of this paper are found to be robust and more efficient than contemporary approaches.     

船舶溢油应急反应人的可靠性分析研究

为减小船舶溢油事故应急反应人员失误概率,提升应急处置效果,在对应急人员可靠性主要影响因素识别的基础上,利用模糊贝叶斯网络(BN)建立船舶溢油应急人的可靠性分析(HRA)模型,将应急反应流程抽象为可进行概率推算的BN,实现单个应急任务和全过程人的可靠性的量化评估,并依据该模型对一起船舶溢油事故进行实例研究。结果表明,首先模糊集值专家评估较好地解决应急人员可靠性情境依赖性强,难以量化评估的问题;其次,BN卓越的概率推理性能实现由单个应急任务向全过程人的可靠性的推算;最后得到应急反应人的可靠性主要取决于关键应急任务的完成情况和相关情境因素的影响。     

基于在线检测信息的储罐底板腐蚀状态智能评价方法

为了解决利用声发射在线检测技术对储罐底板腐蚀状态进行评价时,主要依赖检测人员经验的问题,使该项技术能更好地推广和应用,利用储罐底板在线检测的声发射信息和外观检查信息,并根据相关标准及专家经验,确定与储罐底板腐蚀状态相关的表征因素。采用遗传算法(GA)改进贝叶斯网络(BN)搜索方法,建立基于GA的BN智能评价方法。针对声发射在线检测信息和外观检查信息,分别建立基于标准用声发射因素、基于声发射因素和综合考虑声发射因素和外观检查因素的基于在线检测信息的储罐底板腐蚀状态评价模型。通过对测试样本的评价,对比声发射检测专家评价结果,其中基于在线检测信息的储罐底板腐蚀状态评价模型的准确率为96%,该模型能够对储罐底板腐蚀状态进行可靠的智能评价。