基于自适应网络模糊推理方法在河道洪水预报中的应用

对于易受洪灾的地区而言,快速而准确的洪水预报非常重要,能够为洪水预警消息的发布提供更长的先导时间,从而为可能受灾地区的人们提供更充足的时间以采取相应的防洪措施或安全转移。 常用的预报模型包括基于物理性模型和基于系统技术模型。尽管物理性模型能对洪水形成的物理过程提供很好的解释, 水文学家并不愿意使用它们,因为模型中参数的率定是比较复杂的。因此,一种基于纯数据集的黑箱技术已被广泛采纳。常用的黑箱模型包括线性模型(LR)、自回归移动平均模型(ARMA)和人工神经网络模型（ANN）等。 在当前的研究中,一个相对新颖的黑箱模型--基于自适应网络的模糊推理系统（ANFIS）被用来对长江某河段的洪水进行预报。与此同时,一个线性回归模型（LR）用来作为ANFIS模型的对照。在构建ANFIS中,混合学习算法 (即误差反衍（BP）耦合最小二乘法（LSE）) 用来训练模型的参数。此外,为避免出现过度训练现象,原始数据集基于统计特征值划分成3个子集：训练集、测试集和校正集。当对ANFIS模型训练时,测试集用来帮助控制训练代数。结果表明,ANFIS的预报效果优于LR模型。分析认为ANFIS能够提供预报精度是因为其采用了局部拟合技术,通常它会优于LR模型所采用的全局拟合技术。最后,对本研究而言,最适合的ANFIS模型是输入量为梯形的成员度函数。     

Urban meteorological modelling for nuclear emergency preparedness

The main objectives of the current EU project “Integrated Systems for Forecasting Urban Meteorology, Air Pollution and Population Exposure” (FUMAPEX) are the improvement of meteorological forecasts for urban areas, the connection of numerical weather prediction (NWP) models to urban air pollution and population dose models, the building of improved urban air quality information and forecasting systems, and their application in cities in various European climates. In addition to the forecast of the worst air-pollution episodes in large cities, the potential use of improved weather forecasts for nuclear emergency management in urban areas, in case of hazardous releases from nuclear accidents or terror acts, is considered. Such use of NWP data is tested for the Copenhagen metropolitan area and the Øresund region.The Danish Meteorological Institute (DMI) is running an experimental version of the HIRLAM NWP model over Zealand including the Copenhagen metropolitan area with a horizontal resolution of 1.4 km, thus approaching the city-scale. This involves 1-km resolution physiographic data with implications for the urban surface parameters, e.g. surface fluxes, roughness length and albedo. For the city of Copenhagen, the enhanced high-resolution NWP forecasting will be provided to demonstrate the improved dispersion forecasting capabilities of the Danish nuclear emergency preparedness decision–support system, the Accident Reporting and Guidance Operational System (ARGOS), used by the Danish Emergency Management Agency (DEMA).Recently, ARGOS has been extended with a capability of real-time calculation of regional-scale atmospheric dispersion of radioactive material from accidental releases. This is effectuated through on-line interfacing with the Danish Emergency Response Model of the Atmosphere (DERMA), which is run at DMI. For local-scale modelling of atmospheric dispersion, ARGOS utilises the Local-Scale Model Chain (LSMC), which makes use of high-resolution DMI-HIRLAM NWP model data provided to DEMA by DMI four times a day under operational surveillance and covering Denmark and surroundings. The integration of DERMA in ARGOS is effectuated through automated on-line digital communication and exchange of data. The calculations are carried out in parallel for each NWP model to which DMI has access, thereby providing a mini-ensemble of dispersion forecasts for the emergency management.     

长沙市两种空气质量预报方法检验对比

为探索新的空气质量预报方法，提高预报准确率，采用统计和对比方法，分析了长沙市空气质量现状，介绍了天气形势相似及动态逐步回归两种空气质量统计预报方法，并对其一年多的运行结果进行了检验和对比。结果表明，长沙市空气污染主要由PM\-\{10\}和SO\-2浓度超标引起, 且具有明显的空间分布特征;5年来长沙城市空气质量明显好转;两种预报方法对各污染物都有一定的预报能力，预报的误差绝对值多集中在30以内，而级别误差基本上在1级以内。两种方法对NO\-2的预报准确率均在98%左右,预报效果优良。绝对误差对比发现，两种预报方法对SO\-2的预报明显优于PM\-\{10\}预报；级别准确率对比时，两种预报方法对3种污染物的预报准确率相近。两种预报方法对3个污染因子的预报准确率呈现出NO\-2优于SO\-2优于PM\-\{10\}的趋势。     

改进的最优组合人口预测模型及其应用

人口预测是编制土地利用总体规划的基础性研究工作,区域人口发展规模和数量是土地利用总体规划中确定各类用地控制指标和调整土地利用结构的重要依据。因此,科学准确地预测人口发展,是制定区域土地利用总体规划的基础。在分析各种人口预测模型的基础上,提出了一种改进的最优组合模型。并以湖南省张家界市永定区人口预测为例,利用改进的最优组合模型进行了人口模型预测,并与现有的线性回归模型、灰色系统GM(1,1)模型、logistic 模型、最优组合模型的预测结果进行了对比分析。结果表明,提出的改进的最优组合模型预测结果准确可靠,有利于土地管理的科学决策,是适宜于区域土地利用规划中总人口预测的一种较好的方法。     

基于高斯过程回归模型的洪涝灾害损失预测研究——以重庆市为例

快速准确的预测洪涝灾害各项损失是开展洪涝灾害应急管理工作的基础,而预测技术和方法则是洪涝灾害损失预测的核心与关键。从灾害风险构成因素和数据易获取性2方面构建了洪涝灾害损失评估指标体系,分别从致灾因子、孕灾环境、承灾体和应急能力4个方面选取了13项损失评估输入指标,提出基于高斯过程回归模型的洪涝灾害损失预测方法,并应用于重庆市洪灾受灾人数、农作物受灾面积和直接经济损失的预测。实例表明,高斯过程回归方法对上文提到的3种损失情况预测结果的残差平方和分别为0.99、0.1、12.67,拟合精度分别达到99.85%、99.97%、96.1%,相较于多层感知器神经网络和支持向量机等方法更具优越性。     

长江湖北段干堤整险加固的现状与思考

通过对１９９８ 年长江全流域特大洪水成因和汛在贯彻中央“３２”字治水方针，采用新技术、新方法、新工艺、新材料整治险工险段，加固长江干堤进展情况的调查与分析，阐述了利用高新技术对长江干堤进行整险加固的必要性和可能性及其现状，并就今后如何采用高新技术加固长江干堤，确保堤防工程体系工程质量，建立相应的安全实时监测体系和开展防汛抗洪中的关键实用技术研究开发如基于３Ｓ技术的雨情、汛情、工情、灾情的预测、预报及评估、决策支撑体系的应用与推广，堤防工程隐患的探测、监视、诊断与险情、险段的抢护整治加固材料和技术的开发与推广，洪泛敏感区工农业结构和种养模式的优化、示范与推广等等问题，提出了建设性意见     

The use of a Delphi consultation to explore the curriculum for sustainable development in engineering

Developing a curriculum for sustainable development for engineers, even on a small scale, is a complex task. The University of Manchester has been undertaking a pilot project for an experiential, student-centred approach across engineering and science disciplines, described elsewhere. But that pilot also provided a springboard for the study described in this article. Group techniques for resolving complex issues have been around for half a century but mostly applied to questions of forecasting. Of these, the Delphi technique seemed to best fit the curriculum issues that we wished to explore. This article sets out some of the background to the choice of the Delphi approach, the questions that we sought to answer, the responses that we obtained and some discussion of the appropriateness of the approach to other issues of sustainable development and curriculum design.     

Rural households’ livelihoods diversification through termite utilization in depressed region of Zimbabwe

This study sought to examine the utility of termites to rural households in depressed regions of Bikita, Zimbabwe. Colonialism and its spread of European culture had viewed entomophagy with contempt resulting in reduced utilization and consumption of termites in most colonies. In our quest to understand how people in depressed regions utilized termites, both quantitative and qualitative methodologies were employed. Questionnaires and in-depth interviews were used to gather data during field work. Purposive and snowball sampling techniques were used in recruiting respondents. Excel and content analysis were used in data presentation and analysis. Results revealed that dampwood and drywood termites are climatic indicators for the rural communal farmers, a low-cost technology in weather forecasting. Subterrain and mold builders provide manure, relish, and are medicinal in nature. They are traded for income generation, and as for the poor, harvesting, processing, storage, and marketing is cost effective. Though considered nostalgic foods, most respondents highlighted that selling termites complimented other off-farm livelihood activities. Termite consumption and utilization provide a sustainable way for livelihood diversification in depressed regions and has partly addressed problems of food insecurity.     

基于组合模型的能源需求预测

能源是人类生存和发展的重要物质基础,也是当今国际政治、经济、军事、外交关注的焦点。能源需求预测是合理制定能源规划的基础。能源需求预测的模型很多,总的来说,可以分为单一模型预测和组合模型预测。本文在分析几种常用单一模型的优缺点和适用范围的基础上,建立BP神经网络与灰色GM的优化组合模型,对江苏省未来十五年煤炭和石油的需求量进行预测。结果表明:①随着经济的发展,未来江苏省对煤炭和石油的需求量逐渐增加,其中煤炭从2008年的19 601.39万t标准煤增加到2020年的25 615.26万t标准煤,年均增长率为1.81%;石油从2008年的2 628.64万t标准煤增加到2020年的3 532.60万t标准煤,年均增长率为1.36%;②基于BP网络与GM(1,1)的组合模型克服了单一模型的缺点,实现了优化组合模型"过去一段时间内组合预测误差最小"的原则,且预测结果误差较小,不仅适用于能源的中长期预测,还可以推广到其他领域。     

A study on forecasting paths of genuine savings and wealth without and with carbon dioxide constraints: development of shadow price functions

This paper has developed a method for forecasting the future paths of genuine savings (GS) with and without carbon dioxide (CO₂) emissions constraints. GS calculations require shadow prices, which can be endogenously determined for variables and constraints in a model. However, in case of a ‘business as usual’ model (BAU), the shadow prices required for calculating GS without constraints show theoretically zero. This research derives the shadow prices required to measure GS for the BAU case as a function of several variables available in the optimal (economically efficient) case. This function is estimated from endogenously obtained variables from a model with environmental constraints. Subsequently, this function is used to calculate shadow prices with and without CO₂ constraints, which are further employed to compute future paths of GS according to two methods applied in the papers by Arrow et al. We successfully estimated GS (or GSnt; GS with changes in population and technology) under the BAU case, however, suggest that GS (or GSnt) measures depend, to a great extent, on the time span under consideration (truncation year) for wealth accounting and the accounting methods by Arrows’ papers used for its estimation. In some cases, especially according to the methodology used by Arrow’s paper in 2004 using adjusted consumption in wealth accounting, the sign of GS (or GSnt) changes from negative to positive when changes in total factor productivity are taken into consideration. These aspects should be explored before measuring (un)sustainability of a particular path based on the GS (or GSnt) indicator.     

Influence of global warming on coastal infrastructural instability

The increasing infrastructure instability is an important issue in relation to the influences of global climate change in urban areas. A serious issue pertaining to this is the dual nature of damage triggered by events combined with climate change and natural hazards. For example, catastrophic damage could result from the combination of global warming with a great earthquake, which is a worst-case scenario. Although this worst-case scenario has rarely occurred and presents a low probability of occurrence, countermeasures must be prepared in advance based on an appropriate response and adaptation strategies. After an overview of possible infrastructural instabilities caused by global warming, methodologies are proposed placing emphasis on the increasing probability of infrastructural instability triggered by natural hazards resulting from groundwater-level (GWL) variations. These effects are expected to be particularly serious in coastal regions because of the influence of the rising sea level resulting from global warming. The influence of sea-level rises (SLR) will become apparent along with land subsidence because groundwater abstraction will become severe in coastal regions. Additionally, the probability of earthquake liquefaction increases if GWL rises in accompaniment with SLR. Using case histories, we examined the possible occurrence of these natural hazards as a result of global warming. Finally, possible countermeasures and adaptation strategies for reducing and mitigating infrastructure damage accelerated by global warming are described for each case in specific regions. In particular, special attention should be paid to adaptation strategies in coastal lowlands, which particularly suffer from the effects of land subsidence.     

Box models for the CO2 cycle of the earth

Box models for the global CO₂-cycle are described by a system of first order linear differential equations with constant coefficients. Conditions for uniquely existing equilibrium states are given and the reaction to disturbances is analysed. Kalman filtering techniques are applied to uncertainty problems. Some numerical calculations are presented for illustration purposes.     

统计降尺度在AREM模式洪水预报试验中应用初探

利用2006~2008年AREM模式预报降雨和漳河水库逐小时雨量站观测降雨及入库流量资料,对水库流域进行网格划分,建立了基于网格的空间分辨率分别为(0.25°×0.25°)和(0.5°×0.5°)的降雨预报统计降尺度模型,同时对降尺度模型了进行了模拟效果的检验,证明该降尺度模型的计算结果可以用于漳河水库洪水预报试验。从2009~2010年中选取了4次洪水过程,进行个例试验,试验结果表明,统计降尺度模型对洪水过程效率系数的改进效果不明显,但对减小预报洪峰流量相对误差有一定的效果,平均相对误差降低了10%左右,峰现时差也略有减小。     

Chemical plant risk assessment: Uncertainties and development needs

A brief review is given covering the development of major hazards risk assessment since the Flixborough disaster of 1974, with special reference to the introduction of new regulations. The importance of risk assessment in the management of major hazards is discussed by reference to the Canvey Island studies, and it is suggested that the problem of uncertainties in the estimation of risks by analysis has not been adequately treated. Examples are given to illustrate the magnitude of such uncertainties in the consequence modelling of accidental releases from a chemical plant. In addition to suggested development needs in risk analysis techniques, topics are suggested which call for development in the evaluation and management of risks.     

Determination of brominated flame retardants,with emphasis on polybrominated diphenyl ethers (PBDEs) in environmental and human samples--a review

Analytical methods for the determination of brominated flame retardants (BFRs), with a special emphasis on polybrominated diphenyl ethers (PBDEs) are reviewed. A number of procedures, which can be applied to the analysis of PBDEs and polybrominated biphenyls (PBBs), and in some cases for hexabromocyclododecane (HBCD), in environmental and human samples are described. Because several BFRs, such as tetrabromobisphenol-A (TBBP-A), BDE 209 and, to some extent, HBCD, may require a different approach, specific advice on their analysis is given separately when needed. Sample pretreatment, extraction, cleanup and fractionation, injection techniques, chromatographic separation, detection methods, quality control and method validation are discussed. For each topic, an overview is given of the current status of the field and recommendations for an appropriate analytical approach are presented.     

基于EFDC和WASP模型的突发水污染事故影响的预测预警

近年来,我国突发水污染事故频发。长江作为我国最重要的水源地,其水质安全受到沿江众多化工企业可能突发污染事故的威胁。因此,开展南京化工园突发水污染事故影响的预测预警研究意义重大。基于EFDC和WASP模型,建立了南京化工园突发水污染事故影响的预测模型,并以龙翔甲苯罐区泄漏为例进行了事故情景模拟。研究表明：所建的预测模型能够对南京化工园突发水污染事故后污染物的水环境行为进行快速的模拟和预测,并且能够在地理信息系统的图层上以动画的形式实时展示事故影响的范围和程度,可以为南京化工园突发水污染事故的预警应急提供决策依据;基于EFDC构建的二维水动力模型能够较为准确地反映研究区的水动力情况;事故情景中排放的甲苯在研究江段能够较快地稀释扩散,挥发作用对甲苯的衰减过程影响显著,平水期比枯水期更有利于水体中甲苯的衰减     

Forecasting energy demand of China using Bayesian Combination model

To analyze the impact of the related economic factors on China's energy demand, Path analysis is used to analyze the major factors and their direct and indirect effects on energy demand. This study showed that the main factors that affect the energy demand are the economic growth, the total population, and the primary energy structure, the economic growth is the main determining factor, and the primary energy structure is the major restrictive factor. On this basis and considering the multicollinearity and the validity of the forecast, we established a partial least-square (PLS) and the trend extrapolation prediction model, and then we sum up all the information to found a PLS—trend extrapolation combination forecasting model based on the optimized combining forecast theory. Finally, we obtain the probability distribution of the error using the Bayesian statistic theory and find the confidence interval of combining forecasting result. The results indicate that the outcome of combining forecasting will be more precise after using the Bayesian error correction approach.     

Characterization of hydrocarbon pollutant burdens in petrochemical and refinery process streams

This paper describes techniques which provide for both qualitative and quantitative identification of major components in a process stream. The techniques and instrumentation have been deliberately chosen so as to be within the technical and financial reach of all but the smallecompany laboratory. The sample preparation steps consist of an initial series of extractions which isolate compounds into organic acid, base, and neutral compounds and a totally water soluble phase. Each fraction is then concentrated and subjected to thin-layer chromatography, gas chromatography, infrared spectroscopy or ultraviolet spectroscopy as appropriate. Results are given for laboratory samples, one a mixture of aniline, phenol, benzoic acid, m-nitrobenzaldehyde, 1-butanol, 2-hexanone, nonane, and cyclohexane, and the other a mixture of benzene, ethylbenzene, and styrene. Also, a qualitative analysis of a petroleum refinery desalter water is presented.     

武汉市灰霾天气特征分析及基于支持向量机的能见度预报

利用武汉市2013年灰霾日气象数据和空气质量数据对灰霾天气特征及其影响因子进行了综合研究,获得了武汉市灰霾天气的主要影响因子,并使用支持向量机对灰霾日能见度进行了多因子综合预测。实验表明,支持向量机模型在短期预报中,±1 km、±2 km、±3 km误差范围内预报正确率分别达到733%、867%、967%,平均绝对误差在1 km内,实现了灰霾能见度高精度预报,优于多种预报模型。在第2、3天±3 km误差范围内的能见度预报准确率都达到90%,中长期预报能力较强,模型性能稳定