残矿回采地压安全预警系统的构建方法与应用研究

为提高矿山的安全生产水平,针对地下矿山复杂环境下残矿回采过程潜在的安全问题,并基于安全系统工程的观点与粗糙集理论的属性约简功能,提出残矿回采地压安全预警系统的构成内容与构建流程,建立地压监测数据的神经网络灰色Verhulst算法组合预测模型和安全评价模型。据此,构建国内某矿山残矿回采中段的地压安全预警系统,该地压安全预警系统为本矿山的残矿回采过程提供了安全保障。残矿回采地压安全预警系统能指导矿山循序渐进的构建符合残采系统工程实际的安全预警系统。     

On the Food Disasters in the Lower Jingjiang Reaches: Grey Prediction Model and Application

In the light of the historical substantial data (covering a 70-year period) collected in the Lower Jingjiang segment and aided by topological grey method, here we attempt to characterize the occurrence and future trend of flood calamities in the study area. Our findings indicate that overall the high-frequent flood disasters with middle to lower damage prevail at present. A series of dramatic flood waves will appear in the years of 2016, 2022, 2030and 2042, particularly a destructive flood will occur between 2041 and 2045 in the Lower Jingjiang reaches. Typical of sensitive response to flood hazards in close association with its special geographical location, the lower Jingjiang segment hereby can reflect the development trend of floods in the middle Yangtze reaches. According to the results, a good fitness was revealed between the prediction and practical values. This actually hints that the topological grey method is an effective mathematical means of resolving problems containing uncertainty and indetermination, thus providing valuable information for the flood prediction in the middle Yangtze catchment.     

西北干旱灾害影响因子分析

干旱是西北地区最严重的灾害，利用西北地区降水和农作物旱灾面积统计资料，将干旱灾害事件与影响因子进行对比分析，结果表明：厄尔尼诺事件当年或次年，南方涛动指数负距平，太阳黑子低值，青藏高原为多雪年，地表径流枯期，西北干旱灾害发生率较高。     

港口石油化工码头及其库区灾害事故应急系统研究

通过对石油化工码头及其库区危险因素的分析,提出编制应急预案重点要考虑的问题是:明确重大危险源性质与布局;灾害事故的类型及规模;灾害事故等级的划分;一旦发生灾害事故,谁来指挥,谁来救灾,拿什么救灾,怎么救灾的应急反应机制和整个应急过程的通讯联络。为使应急预案具有可操作性,提出了预案编制要点。石油化工码头及库区灾害事故应急系统除编制灾害事故应急预案外,还应实施由重大危险源电子地图信息管理,油品(化学品)的理化特性、应急处理方法及防护措施基本信息查询,可燃有毒气体泄漏扩散模拟预测和池火热辐射强度模拟预测等组成的危险源管理地理信息系统和灾害事故灾情快速预测系统。     

Water,Adaptation, and Property Rights on the Snake and Klamath Rivers1

Abstract: Water demand in a viable economy tends to be dynamic: it changes over time in response to growth, drought, and social policy. Institutional capacity to re‐allocate water between users and uses under stress from multiple sources is a key concern. Climate change threatens to add to those stresses in snowmelt systems by changing the timing of runoff and possibly increasing the severity and duration of drought. This article examines Snake and Klamath River institutions for their ability to resolve conflict induced by demand growth, drought, and environmental constraints on water use. The study finds that private ownership of water rights has been a major positive factor in successful adaptation, by providing the basis for water marketing and by promoting the use of negotiation and markets rather than politics to resolve water conflict.     

Field‐Scale Application of Three Types of Neural Networks to Predict Ground‐Water Levels1

Abstract: In this paper, a field‐scale applicability of three forms of artificial neural network algorithms in forecasting short‐term ground‐water levels at specific control points is presented. These algorithms are the feed‐forward back propagation (FFBP), radial basis networks (RBN), and generalized regression networks (GRN). Ground‐water level predictions from these algorithms are in turn to be used in an Optimized Regional Operations Plan that prescribes scheduled wellfield production for the coming four weeks. These models are up against each other for their accuracy of ground‐water level predictions on lead times ranging from a week to four weeks, ease of implementation, and execution times (mainly training time). In total, 208 networks of each of the three algorithms were developed for the study. It is shown that although learning algorithms have emerged as a viable solution at field scale much larger than previously studied, no single algorithm performs consistently better than others on all the criteria. On average, FFBP networks are 20 and 26%, respectively, more accurate than RBN and GRN in forecasting one week ahead water levels and this advantage drops to 5 and 9% accuracy in forecasting four weeks ahead water levels, whereas GRN posted a training time that is only 5% of the training time taken by that of FFBP networks. This may suggest that in field‐scale applications one may have to trade between the type of algorithm to be used and the degree to which a given objective is honored.     

云南省交通事故数据的分析研究

通过对云南省1981—2003年的交通事故统计数据的分析研究,给出了交通事故死亡人数的预测模型。通过与发达国家类似的交通事故历史数据的对比分析,给出以时间和机动车拥有量为自变量、交通事故死亡人数为因变量的简单预测模型,该模型对2004年的交通事故死亡人数的预测是准确的;同时采用该模型预测了云南省交通事故死亡人数的峰值及其年份。结论指出:基于目前的人、车、路和管理水平及发展趋势,云南省的交通事故死亡人数在2013—2018年之间将达到高峰,高峰时的交通事故死亡人数在5528～7369人之间。     

多目标决策的农业抗旱能力综合评价

利用灰色系统理论中的关联分析建立了湖南农业抗旱能力评价的指标体系,运用多目标决策法对湖南14个市州的抗旱能力进行了评价。其结果是:在三种方案中娄底(1.452 9)、邵阳(1.398 8)、常德(1.580 2)的抗旱能力综合指数最大,抗旱能力强;而张家界在3种方案中抗旱能力综合指数都小于0.5,抗旱能力弱。并为湖南抗旱减灾、提高抗旱能力提出了合理的建议与对策。     

黑龙江省暴雪天气分析和预报技术

分析表明，造成黑龙江省暴雪的低压天气系统不仅来自西北、偏西和偏南方向，而且还有在东北和日本海新生成的，其中又以西南和南来的居多；高空影响系统主要是低槽，其次是低涡，但降暴雪时多数是低涡；造成暴雪的锋面系统以暖锋和锢囚锋为最多。另外，从造成降水的成因和水平锋生这两个角度出发，给出了7个暴雪落区的温压场模型。850hPa温度、850hPa温度平流和拔海高度决定了降水（雨、雪）的性质。