梨园杀虫剂的环境风险评价

评价了某雪花梨栽培试验园区施用的杀虫剂对周围环境的风险性。其中包括；利用化学物质排毒系数评价法对梨园杀虫剂进行初步风险识别；非突发性水环境污染风险分析。采用瞬时点源一维河流模型对杀虫剂因事故性泄漏水体造成的风险进行预测；简要说明了杀虫剂进入土壤的途径及其对施药区和非施药区土壤的危害；采用高斯烟团模式，通过大气取样，对杀虫剂超常量喷施进入大气捕捞浓度分布进行统计分析，测算出杀虫剂在不同浓度范围出现的相对频率，从而鉴别其对居民点空气质量的危害几率。     

降低企业库存风险问题研究

大多数企业都面临着库存风险问题 ,库存过多 ,造成积压 ,不仅占用大量资金和场地 ,加重企业的利息负担 ,而且长期存放会使物品陈旧过时 ,失去原有的价值和使用价值。如何降低库存风险 ,使库存经常处于合理水平 ,是每个企业都十分关心的问题。笔者分析了库存管理中存在的问题 ,提出需求预测和安全库存的确定 ,是降低库存风险的两个重要前提 ,同时讨论了安全库存的计算方法 ,以及降低库存风险的主要措施     

甲撑二苯基二异氰酸酯(MDI)生产过程中危险有害因素及对策措施

甲撑二苯基二异氰酸酯 (MDI)生产过程中涉及到了多种危险有害因素。笔者通过对国内现役MDI生产装置进行调研 ,同时结合国内外其他涉及光气生产厂家的情况 ,分析并指出了生产过程中可能出现的危险有害因素 ,从而提出了相应的对策措施     

太湖流域主要城市洪涝灾害生态风险评价

太湖流域有上海，苏州，无锡，常州，镇江，杭州，嘉兴，湖州八个大中城市，是我国产业最集中，工农业最发达的地区之一，但该地区洪涝灾害频繁，这不仅制约了流域中各城市经济的发展，还严重威胁到该地区城市的生存平衡，本文根据生存风险评价原理，结合太湖流域的自然特点，提出成因分析法的指标模型。并通过分析太湖流域八个大中城市的汛期降雨量和地形地貌因子对洪涝灾害生态风险的影响度，得出各个城市洪涝灾害的生态风险度，最后还根据各城市风险度的大小及其主导因素的不同，提出了如何管理洪涝灾害生态风险的建议。     

中国东南沿海重点城市台风危险性分析

中国东南沿海地区是中国经济最发达，人口最稠密的地区，同时也是世界上受台风影响最严重的地区之一。本文以上海经9个沿海重点为例，通过对《台风年鉴》数据的分析处理，提取了台风关键参数并进行了统计分析与建模；利用Monte Carlo抽样和成熟台风风场模型模拟，得到了极值风速序列，对年极值风速序列进行极值风速统计分析，得到了不同重现期和地貌的极值风速，结果与实测风速比较吻合。     

A comparative study of risk perception in small and large communities where chemical industries are present

Opinion polls were conducted to assess the level of risk perceived by the citizens in communities of different sizes where chemical industries were present. The aim of the study was to relate the risk perceived to variables such as the nature of risks, the specific information received regarding the industrial activity and the economic impact of this activity in the community.     

FLOOD STAGE FORECASTING WITH SUPPORT VECTOR MACHINES1

ABSTRACT: Machine learning techniques are finding more and more applications in the field of forecasting. A novel regression technique, called Support Vector Machine (SVM), based on the statistical learning theory is explored in this study. SVM is based on the principle of Structural Risk Minimization as opposed to the principle of Empirical Risk Minimization espoused by conventional regression techniques. The flood data at Dhaka, Bangladesh, are used in this study to demonstrate the forecasting capabilities of SVM. The result is compared with that of Artificial Neural Network (ANN) based model for one‐lead day to seven‐lead day forecasting. The improvements in maximum predicted water level errors by SVM over ANN for four‐lead day to seven‐lead day are 9.6 cm, 22.6 cm, 4.9 cm and 15.7 cm, respectively. The result shows that the prediction accuracy of SVM is at least as good as and in some cases (particularly at higher lead days) actually better than that of ANN, yet it offers advantages over many of the limitations of ANN, for example in arriving at ANN's optimal network architecture and choosing useful training set. Thus, SVM appears to be a very promising prediction tool.     

THE DEVELOPMENT OF A MODEL TO EVALUATE HYDROLOGIC RISK IN WATER RESOURCE SYSTEM DESIGN1

In this paper, a procedure for analyzing a water resource system with special emphasis on evaluation of acceptable economic risk due to occasional failures to deliver water is proposed. The basic methodology includes the development of a simple mathematical model which describes the physical hydrologic and economic characteristics of a single reservoir irrigation and city water supply system and an evaluation of economic benefits of the system with full and partial deliveries of water. The system is simulated for various combinations of decision variables (system magnitudes) and an optimum design is obtained by response surface technology. Emphasis is placed on the basic model and methodology although, in order to introduce some realism, the procedure is applied to data based on the existing reservoir system on the South Concho River in West Central Texas.