层次分析法的改进及在安全决策中应用的研究

本文根据化工行业的特点及调研资料,建立了影响安全的层次结构模型即安全指标体系。并利用改进式层次分析法（IAHP）对该体系进行分析,得出了各个因素对安全的影响系数（权重）。     

A Complex Systems Model Approach to Quantified Mineral Resource Appraisal

For federal and state land management agencies, mineral resource appraisal has evolved from value-based to outcome-based procedures wherein the consequences of resource development are compared with those of other management options. Complex systems modeling is proposed as a general framework in which to build models that can evaluate outcomes. Three frequently used methods of mineral resource appraisal (subjective probabilistic estimates, weights of evidence modeling, and fuzzy logic modeling) are discussed to obtain insight into methods of incorporating complexity into mineral resource appraisal models. Fuzzy logic and weights of evidence are most easily utilized in complex systems models. A fundamental product of new appraisals is the production of reusable, accessible databases and methodologies so that appraisals can easily be repeated with new or refined data. The data are representations of complex systems and must be so regarded if all of their information content is to be utilized.The proposed generalized model framework is applicable to mineral assessment and other geoscience problems. We begin with a (fuzzy) cognitive map using (+1,0,–1) values for the links and evaluate the map for various scenarios to obtain a ranking of the importance of various links. Fieldwork and modeling studies identify important links and help identify unanticipated links. Next, the links are given membership functions in accordance with the data. Finally, processes are associated with the links; ideally, the controlling physical and chemical events and equations are found for each link. After calibration and testing, this complex systems model is used for predictions under various scenarios. Published on line     

A GIS analysis of suitability for construction aggregate recycling sites using regional transportation network and population density features

Aggregate is used in road and building construction to provide bulk, strength, support, and wear resistance. Reclaimed asphalt pavement (RAP) and reclaimed Portland cement concrete (RPCC) are abundant and available sources of recycled aggregate. In this paper, current aggregate production operations in Virginia, Maryland, and the District of Columbia are used to develop spatial association models for the recycled aggregate industry with regional transportation network and population density features.The cost of construction aggregate to the end user is strongly influenced by the cost of transporting processed aggregate from the production site to the construction site. More than 60% of operations recycling aggregate in the mid-Atlantic study area are located within 4.8 km (3 miles) of an interstate highway. Transportation corridors provide both sites of likely road construction where aggregate is used and an efficient means to move both materials and on-site processing equipment back and forth from various work sites to the recycling operations.Urban and developing areas provide a high market demand for aggregate and a ready source of construction debris that may be processed into recycled aggregate. Most aggregate recycling operators in the study area are sited in counties with population densities exceeding 77 people/km² (200 people/mile²). No aggregate recycling operations are sited in counties with less than 19 people/km² (50 people/mile²), reflecting the lack of sufficient long-term sources of construction debris to be used as an aggregate source, as well as the lack of a sufficient market demand for aggregate in most rural areas to locate a recycling operation there or justify the required investment in the equipment to process and produce recycled aggregate.Weights of evidence analyses (WofE), measuring correlation on an area-normalized basis, and weighted logistic regression (WLR), are used to model the distribution of RAP and RPCC operations relative to transportation network and population distribution data. The models can be used on a regional scale to quickly map the relative site suitability for a RAP or RPCC aggregate recycling operation in a particular area based on transportation network and population parameters. The results can be used to identify general areas to be further evaluated on a site-specific basis using more detailed marketplace information. As transportation or population features change due to planning or actual development, the models can be easily revised to reflect these changes.     

Spatial and statistical assessment of factors influencing nitrate contamination in groundwater

The weights of evidence (WofE) modeling technique has been used to analyze both natural and anthropogenic factors influencing the occurrence of high nitrate concentrations in groundwater resources located in the central part of the Po Plain (Northern Italy). The proposed methodology applied in the Lodi District combines measurements of nitrate concentrations, carried out by means of a monitoring net of 69 wells, with spatial data representing both categorical and numerical variables. These variables describe either potential sources of nitrate and the relative ease with which it may migrate towards groundwater. They include population density, nitrogen fertilizer loading, groundwater recharge, soil protective capacity, vadose zone permeability, groundwater depth, and saturated zone permeability. Once conditional dependence problems among factors have been solved and validation tests performed, the statistical approach has highlighted negative and positive correlations between geoenvironmental factors and nitrate concentration in groundwater. These results have been achieved analysing the calculated statistical parameters (weights, contrasts, normalized contrasts) of each class by which each factor has been previously subdivided. This has permitted to outline: the overall influence each factor has on the presence/absence of nitrate; the range of their values mostly influencing this presence/absence; the most and least critical combination of factor classes existing in each specific zone; areas where the influence of impacting factor classes is reduced by the presence of not impacting factor classes. This last aspect could represent an important support for a correct land use management to preserve groundwater quality.     

基于多层次灰色评价理论的海洋输油管道安全评估方法

针对海上输油管道在多层次、多变量、多种非定量因素的影响下缺乏有效定量评估手段的情况,建立输油管道体系的多层次安全评估指标,结合层次分析法,确定各层指标对应的权重,提出采用多层次灰色理论,对输油管道体系进行安全评估,将风险影响程度进行定量化处理,给出了在役输油管道的可靠性量化结果。多层次灰色评估方法针对少数据、小样本、信息不完全和经验缺乏的不确定性问题有着计算简便、直接、科学和实用的特点,可为海上输油管道的在役安全评估提供一种有效手段。     

Spatial modelling of socioeconomic data to understand patterns of human-caused wildfire ignition risk in the SW of Madrid (central Spain)

The majority of wildfires in the Mediterranean Basin are caused directly or indirectly by human activity. Many biophysical and socioeconomic factors have been used in quantitative analyses of wildfire risk. However, the importance and effects of socioeconomic factors in spatial modelling have been given inadequate attention. In this paper, we use different approaches to spatially model our data to examine the influence of human activity on wildfire ignition in the south west of the Madrid region, central Spain. We examine the utility of choropleth and dasymetric mapping with both Euclidean and functional distance surfaces for two differently defined wildfire seasons. We use a method from Bayesian statistics, the Weights of Evidence model, and produce ten predictive maps of wildfire risk: (1) five maps for a two-month fire season combining datasets of evidence variables and (2) five maps for the four-month fire season using the same dataset combinations. We find that the models produced from a choropleth mapping approach with spatial variables using Euclidian and functional distance surfaces are the best of the ten models. Results indicate that spatial patterns of wildfire ignition are strongly associated with human access to the natural landscape. We suggest the methods and results presented will be useful to optimize wildfire prevention resources in areas where human activity and the urban-forest interface are important factors for wildfire ignition.     

证据权法在滑坡易发性分区中的应用——以贵州桐梓河流域为例

应用证据权法对研究区进行滑坡易发性分区。主要数据源有:历史滑坡灾害点编录数据、地质图、地形图、数字高程模型。首先对数据源进行处理,生成地层岩性、离断层距离、高程、坡度、坡向、离道路距离、离河流距离7个证据图层。应用Arc GIS平台,将各证据图层与滑坡灾害点图层进行叠加分析,利用累积权重法对连续数据进行分级,然后求取对连续数据及分类数据因子等级对滑坡灾害贡献的权重值,然后对各证据图层两两进行条件独立性检验,选择4组证据图层组合,参与最终易发性指数计算,得到4幅易发性结果图。应用成功率曲线法对计算结果进行验证,表明由因子组合1得出的计算结果,为最优的因子组合。根据易发性指数将研究区分为高易发性、中等易发性、低易发性三类,并将分区图与历史灾害点进行叠加分析,结果表明评价结果与灾害点分布较为吻合,说明证据权法应用与滑坡灾害易发性分区的可行性。     

Probabilistic Modelling of Cattle Farm Distribution in Australia

A probabilistic Bayesian method called weights of evidence (WofE) was used to develop a synthetic dataset of cattle farm locations at a national scale across Australia. The synthetic dataset was required for the modelling of livestock movements with a view to assessing biosecurity implications. The WofE method is based on the analysis of spatial relationships between evidential patterns with respect to an event, such as the actual location of a farm. The evidential patterns of cattle farms were derived from maps of land use, land tenure, drainage systems, roads, settlements and long-term averaged rainfall. These evidential patterns were used for delineating and ranking land areas suitable for cattle farming. For each evidential pattern statistics such as a positive weight, a negative weight and a contrast were calculated for estimating the degree of correlation between the evidential patterns and known farm locations. The integrated evidential patterns of known farms were then used for estimating posterior probabilities and splitting land into five different classes according to its suitability for farming.

江汉平原地下水中硝酸盐的分布及影响因素

基于2011~2014年825个地下水采样点测试结果,采用半方差函数模型和普通克里格插值方法,研究了江汉平原地下水中NO₃-N的空间变异和分布特征.运用证据权重法,选取降雨入渗补给量、地下水位埋深、渗透系数、包气带岩性、土地利用类型、土壤类型和土壤全氮含量7个因子建立预测模型,分析其对硝酸盐分布的影响规律.结果表明,江汉平原地下水NO₃-N含量经Box-Cox变换后服从正态分布,其半方差函数最佳拟合模型为球状模型,空间相关性为87.93%,相关距离为68.02km.研究区地下水NO₃-N含量具有南部高、北部及西部山前平原低的特点.地下水中NO₃-N含量超过10mg/L分布面积所占比例达8.61%.成功率曲线表明模型预测精度为0.91,预测结果较好.江汉平原地下水NO₃-N含量与该区降雨入渗补给量、渗透系数和土壤全氮含量具有良好的正响应关系,与地下水位埋深呈负响应关系.当包气带岩性为砂砾石、土地利用类型为建设用地及土壤类型为冲积土覆盖条件时,地下水极易受硝酸盐污染.