基于区间直觉模糊信息TODM法的水利工程应急决策研究

为更合理地进行应急方案比选,减少不确定因素和决策者偏好对决策结果的影响,构造了1种更加适应水利工程应急决策的模型。针对应急决策环境的模糊性和不确定性,引入区间直觉模糊集表达评价信息,采用区间直觉模糊熵计算各指标权重;通过构造备选方案两两比较矩阵,运用区间直觉模糊距离测度公式计算方案间的损益值;结合TODIM法计算各方案相对占优度并进行比较排序,确定最优方案。研究结果表明:在损失规避系数确定的前提下,选择任一区间直觉模糊距离公式都不影响方案的优劣排序,决策模型具有一定的可靠性和稳定性。     

Risk assessment of a compound feed process based on HAZOP analysis and linguistic terms

The size and complexity of industrial plants, along with the characteristics of the products used, require a study, analysis and control of the existing risks in every industrial process.In this paper, a methodology for risk assessment in industrial plants, based on the combination of risks identification through the Hazard and Operability (HAZOP) analysis and the risks evaluation through linguistic variables and fuzzy numbers is applied to a case study consisting on a compound feed plant located in the town of Silla (Valencia, Spain).The results from this study show that the main risk in the compound feed production process is the formation of explosive atmospheres (ATEX). Therefore, the corrective measures will focus on reducing the concentration of dust in the atmosphere and eliminating the possible sources of ignition, such as electrostatic discharges or sparks during the different phases of the process (the grinding, the transport of the raw materials, etc.)     

基于可能-概率测度转换的危险品运输风险分析

为解决不确定环境下的风险分析问题,针对危险货物运输中风险参数具有不确定性、随机性和模糊性的特点,建立基于概率测度-可能性测度转换原则和模糊逻辑的危险货物运输风险分析方法。首先对具有模糊性的参数直接建立模糊数,对具有随机性的参数建立随机数;接着依据概率测度向可能性测度转换的最优原则,将随机数转换为模糊数;然后根据模糊运算法则进行风险计算和分析。最后通过一个算例验证了模型和算法的有效性。结果表明,提出的方法能处理随机和模糊环境下的风险分析问题,能为风险分析尽可能多地保留不确定性信息,尽可能少地丢失有用信息。     

中小城市空气环境指标的多角度分析研究——以楚雄市为例

文章根据楚雄市空气污染数据,采用统计的方法从不同的角度探求中小城市空气污染指标的变化规律,并求出三种污染物的同时置信区间及它们之间的关联性。结果表明:楚雄市的空气污染主要由SO2造成,室外空气质量能达到一类地区的水平,三种污染物之间两两相关性较弱,但整体相关性较强,同时根据结论提出了相应的建议。     

SCS URBAN CURVE NUMBERS FROM A LANDSAT DATA BASE1

Estimating the Curve Numbers used in the Soil Conservation Service hydrologic models is a tedious and costly task. Recent advances in remote sensing and data processing have led to the development of readily available land cover data bases for many areas of the United States. This study evaluated the potential of using a Landsat data base to make the Curve Number estimation process more cost-effective and less tedious. Ten watersheds in the Washington, D.C., area were evaluated using a Landsat land cover data base developed by the U.S. Geological Survey. Results showed that these data can be useful. Predictions can be improved if ancillary data on residential lot size are included. It was concluded that this type of data base must be examined carefully before implementation.     

ASSESSMENT OF REMOTE SENSING INPUT TO HYDROLOGIC MODELS1

Remotely sensed variables such as land cover type and snow-cover extent can currently be used directly and effectively in a few specific hydrologic models. Regression models can also be developed using physiographic and snow-cover data to permit estimation of discharge characteristics over extended periods such as a season or year. Most models, however, are not of an appropriate design to readily accept as input the various types of remote sensing parameters that can be obtained now or in the future. Because this new technology has the potential for producing hydrologic data that has significant information content on an areal basis, both inexpensively and repetitively, effort should be devoted now to either modifying existing models or developing new models that can use these data. Minor modifications would at least allow the remote sensing data to be used in an ancillary way to update the model state variables, whereas major structural modifications or new models would permit direct input of the data through remote sensing compatible algorithms. Although current remote sensing inputs to hydrologic models employ only visible and near infrared data, model modification or development should accommodate microwave and thermal infrared data that will be more widely available in the future.     

湿式文丘里除尘工艺改进的应用研究

通过对湖北田力实业股份有限公司麻石(文丘里)水膜除尘工艺在沸腾炉烟气除尘中存在的问题进行研究和分析,对(文丘里)水膜除尘工艺进行了改进。采用加装U型布水装置和采取间歇性用水冲刷灰垢的措施,解决了烟道内壁水、气界面处的结垢问题,替换了人工除垢,且烟尘排放浓度达到了环保要求,其回收的烟尘通过外销又取得了经济效益。     

基于Copula模型的降雨量与土壤饱和度的模拟研究

采用两步法,针对云南东川蒋家沟流域的降雨量与土壤饱和度,建立了边缘为皮尔逊Ⅲ型的Clayton Copula模型,分析了降雨量和土壤饱和度之间相关结构,以及两变量重现期,模拟了流域内土壤饱和度的变化情况。实例表明所构造的Clayton Copula模型能比较好地模拟出流域内土壤饱和度在降雨情况下逐日变化情况,有助于进一步认识降水对土壤饱和度的作用过程,并为分析泥石流灾害的发生提供了一种新思路。     

Flexible interval mixed-integer bi-infinite programming for environmental systems management under uncertainty

A number of inexact programming methods have been developed for municipal solid waste management under uncertainty. However, most of them do not allow the parameters in the objective and constraints of a programming problem to be functional intervals (i.e., the lower and upper bounds of the intervals are functions of impact factors). In this study, a flexible interval mixed-integer bi-infinite programming (FIMIBIP) method is developed in response to the above concern. A case study is also conducted; the solutions are then compared with those obtained from interval mixed-integer bi-infinite programming (IMIBIP) and fuzzy interval mixed-integer programming (FIMIP) methods. It is indicated that the solutions through FIMIBIP can provide decision support for cost-effectively diverting municipal solid waste, and for sizing, timing and siting the facilities’ expansion during the entire planning horizon. These schemes are more flexible than those identified through IMIBIP since the tolerance intervals are introduced to measure the level of constraints satisfaction. The FIMIBIP schemes may also be robust since the solutions are “globally-optimal” under all scenarios caused by the fluctuation of gas/energy prices, while the conventional ones are merely “locally-optimal” under a certain scenario.     

An Inexact Fuzzy-robust Two-stage Programming Model for Managing Sulfur Dioxide Abatement Under Uncertainty

In this study, an inexact fuzzy-robust two-stage programming (IFRTSP) method is developed for tackling multiple forms of uncertainties that can be expressed as discrete intervals, probabilistic distributions and/or fuzzy membership functions. The model can reflect economic penalties of corrective measures against any infeasibilities arising due to a particular realization of system uncertainties. Moreover, the fuzzy decision space can be delimited into a more robust one with the uncertainties being specified through dimensional enlargement of the original fuzzy constraints. A management problem in terms of regional air pollution control has been studied to illustrate the applicability of the proposed approach. Results indicate that useful solutions for planning the air quality management practices have been generated. They can help decision makers identify desired pollution-abatement strategy with minimized system cost and maximized environmental efficiency.