Assessing Risk in Operational Decisions Using Great Lakes Probabilistic Water Level Forecasts

/ A method adapted from the National Weather Service's Extended Streamflow Prediction technique is applied retrospectively to three Great Lakes case studies to show how risk assessment using probabilistic monthly water level forecasts could have contributed to the decision-mak-ing process. The first case study examines the 1985 International Joint Commission (IJC) decision to store water in Lake Superior to reduce high levels on the downstream lakes. Probabilistic forecasts are generated for Lake Superior and Lakes Michigan-Huron and used with riparian inundation value functions to assess the relative impacts of the IJC's decision on riparian interests for both lakes. The second case study evaluates the risk of flooding at Milwaukee, Wisconsin, and the need to implement flood-control projects if Lake Michigan levels were to continue to rise above the October 1986 record. The third case study quantifies the risks of impaired municipal water works operation during the 1964-1965 period of extreme low water levels on Lakes Huron, St. Clair, Erie, and Ontario. Further refinements and other potential applications of the probabilistic forecast technique are discussed.KEY WORDS: Great Lakes; Water levels; Forecasting; Risk; Decision making     

基于GIS的城市环境规划决策支持系统

城市是由于人－地剧烈相互作用而形成的开放的、复杂的社会、经济与环境复合巨系统，在城市环境规划工作中常伴随有大量的结构化、半结构化和非结构化并存的决策问题，这就需要采取人—机交互式的决策支持系统方法来全面支持规划专家的规划活动，同时，城市环境规划本身也是个面向空间实体的操作过程，这也决定了ＧＩＳ将发挥基础性主导工具作用，基于以上两点认识，作者以ＧＩＳ为基本框架，设计了城市环境规划的空间决策支持系统原型方法，实现了城市环境规划数据调查评价、预测、功能区划、规划方案生成与决策、制图等特定功能要求，成为支持城市环境规划的有力工具。     

基于规范变换与误差修正的回归支持向量机的环境系统预测

为了建立不同环境系统皆能规范、统一、简洁、实用的回归支持向量机预测模型,针对传统的回归支持向量机预测模型存在结构不能普适、规范和统一及用于大样本、多因子预测会出现学习效率低、求解精度差的局限,提出适用于环境系统预测量及其影响因子参照值和规范变换式的设计原则和方法,使规范变换后的影响因子皆"等效"于同一个规范影响因子;为提高样本的预测精度,还提出预测样本的模型输出的误差修正法.在对环境系统的预测量及其影响因子进行规范变换的基础上,由有m个规范影响因子的每个建模样本生成m个"等效"训练样本,从建模样本中,选择各影响因子的最大规范值组成训练样本集的"参考样本",计算核函数中每个训练样本相对于"参考样本"的范数;并应用优化算法优化模型参数,建立适用于预测量及其影响因子规范值的仅有2个或3个支持向量的两种简单结构的回归支持向量机预测模型.将基于规范变换的两种简单结构的回归支持向量机模型与相似样本误差修正法相结合,用于河津大桥监测断面6个样本的COD月平均值预测,并与多种传统预测模型和方法进行了比较.结果表明:对同一个预测样本,两种模型的预测值十分接近;此外,两种预测模型用于6个样本预测,其相对误差绝对值的平均值分别为2.09%、2.79%,均远小于传统的投影寻踪回归预测的41.63%、支持向量机预测的40.99%、灰色神经网络预测的25.94%和马尔可夫预测的10.16%;而两种预测模型对异常样本预测的最大的相对误差绝对值分别为5.85%、5.13%,更加远远小于传统的4种预测模型的169.07%、180.45%、68.44%、41.96%.两种基于规范变换的回归支持向量机预测模型简洁、普适、规范和统一,避免了"大样本数困难",提高了学习效率和模型的预测精确度,对其他预测建模法也有借鉴作用.     

基于小波分解与自适应多级残差修正的最小二乘支持向量回归预测模型的PM2.5浓度预测

采用小波分解(WD)将济南市科干所监测站PM_(2.5)浓度的一维时间序列(2013年1月1日—2017年8月15日)分解为高维信息,获得了该监测站附近PM_(2.5)浓度的时频变化特征,重点分析了PM_(2.5)的随机性和趋势性问题.然后构建了基于小波分解的多级残差修正的最小二乘支持向量回归预测模型(AMLRC-WLSSVR),结果发现,该模型能够很好地对济南市PM_(2.5)浓度做出预测,特别是针对重污染天气的预测有很好的精度.为了避免预测结果的不确定性问题,提出了一种基于方差估计给出预测值置信区间上界的方法,同时,有效弥补了单点预测的不稳定性及预测精度不足的缺点,该方法能够为实际空气污染预警提供技术支持.     

A microcomputer-based emergency response system*

A microcomputer-based system was developed to provide local officials responsible for disaster management with assistance during the crucial period immediately following a disaster, a period when incorrect decisions could have an adverse impact on the surrounding community.
While the paper focuses on a potential disaster resulting from an accident at a commercial nuclear power generating facility, the system can be applied to other disastrous situations. Decisions involving evacuation, shelter and the deployment of resources must be made in response to floods, earthquakes, accidents in the transportation of hazardous materials, and hurricanes to name a few examples.
As a decision aid, the system was designed to enhance data display by presenting the data in the form of representations (i.e. road maps, evacuation routes, etc.) as well as in list or tabular form. The potential impact of the event (i.e. the release of radioactive material) was displayed in the form of a cloud, representing the dispersion of the radioactive material. In addition, an algorithm was developed to assist the manager in assigning response resources to demands.
The capability for modelling the impact of a disaster is discussed briefly, with reference to a system installed in the communities surrounding the Indian Point nuclear power plant in New York State.
Results demonstrate both the technical feasibility of incorporating microcomputers indecision support systems for radiological emergency response, and the acceptance of such systems by those public officials responsible for implementing the response plans.     

蜂窝状活性炭研究

蜂窝状活性炭是一种新型的活性炭。简要介绍了蜂窝状活性炭的结构特性和吸附性能，重点总结了蜂窝状活性炭基催化剂的制备方法及其在催化方面的应用。     

SOIL MOISTURE PREDICTION USING SUPPORT VECTOR MACHINES1

ABSTRACT: Herein, a recently developed methodology, Support Vector Machines (SVMs), is presented and applied to the challenge of soil moisture prediction. Support Vector Machines are derived from statistical learning theory and can be used to predict a quantity forward in time based on training that uses past data, hence providing a statistically sound approach to solving inverse problems. The principal strength of SVMs lies in the fact that they employ Structural Risk Minimization (SRM) instead of Empirical Risk Minimization (ERM). The SVMs formulate a quadratic optimization problem that ensures a global optimum, which makes them superior to traditional learning algorithms such as Artificial Neural Networks (ANNs). The resulting model is sparse and not characterized by the “curse of dimensionality.” Soil moisture distribution and variation is helpful in predicting and understanding various hydrologic processes, including weather changes, energy and moisture fluxes, drought, irrigation scheduling, and rainfall/runoff generation. Soil moisture and meteorological data are used to generate SVM predictions for four and seven days ahead. Predictions show good agreement with actual soil moisture measurements. Results from the SVM modeling are compared with predictions obtained from ANN models and show that SVM models performed better for soil moisture forecasting than ANN models.     

小断面锚网支护工作面上下隅角安全问题的探讨

利用事故树对小断面锚网支护方式下,上下隅角的安全问题进行了分析,求出了最小割集和基本事件的结构重要度,提出了防止事故的方案,并在现场应用中取得了良好的效果。     

决策支持系统应用于城市环境管理

南宁市环境决策支持系统集环境管理办公自动化、环境管理系统(MIS)、环境地理信息系统(GIS)、多媒体环境管理信息应用和环境管理信息辅助决策等多功能一体集成的综合性环境信息系统，为南宁市环境管理、经济发展决策提供环境信息支撑与服务。