人工神经网络和专家系统在污水生物处理系统中的应用

对近年来国内外污水生物处理系统中人工神经网络和专家系统的应用进行了简要的回顾。分析了废水生物处理工艺难于控制的原因及人工神经网络和专家系统的结构和特点。结果表明．国外智能控制发展迅速,并且应用领域遍及污水生物处理的各个方面,国内尚处于起步阶段。简要探讨了废水生物处理智能控制今后应深入研究的问题及方向。     

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.     

光纤光栅(FBG)传感器在尾矿库在线监测中的应用

光纤光栅(FGB)传感器已经广泛应用于水利工程监测中,在尾矿库在线监测系统中的应用也在逐步增多。为提高某尾矿库在线监测系统的抗干扰和运行稳定性,某尾矿库在线监测系统工程采用以光纤光栅传感器作为主要采集设备。应用结果表明:光纤光栅传感设备的突出优点是运行稳定性好、抗干扰能力强,测量精度满足使用要求;明显不足是安装条件要求高,前期投入较高。     

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.     

一种pH荧光特性物质的合成及其特性研究

合成并表征了化合物:N,N'-二苯丙氨酸铵-3,4,9,10-苝四羧酸二酰亚胺(PDCDA).研究了pH值变化对其水溶液可见吸收光谱和荧光发射光谱的影响,探讨了荧光强度变化的机理,并利用PDCDA构建了具有“开-关”特性的pH荧光传感器.结果表明,PDCDA化合物水溶性好、荧光量子产率高,荧光强度与pH值间有着强烈的依赖关系,在碱性及中性溶液中荧光强度较强且稳定,而在酸性溶液中荧光被淬灭,PDCDA在一个非常窄的pH范围内荧光强度发生了明显的变化, pH值的改变对发光团π-π堆积产生影响进而导致其荧光发射光谱和可见吸收光谱发生改变.PDCDA可用作水溶液的pH荧光传感器,检测pH值范围为3.8~6.3.     

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.