论北京城市建设的综合减灾问题

本文针对北京城市建设面临的自然与人为灾害背景,简要论述了北京地震、水灾、火灾及“新致灾源”的历史及现状,强调开展首都圈灾害研究及减灾规划设计的重要性,并提出了系统的减灾方略及相应的管理构想。     

基于偏序集的采空区塌陷危险性评价研究

针对采空区塌陷危险性评价方法中的赋权争议问题,基于偏序集理论提出偏序集评价模型。首先阐明评价指标并确定其分级标准;然后应用偏序集评价模型得到Hasse图,并通过图展现的层集信息判别采空区塌陷危险程度;最后应用该模型对大宝山矿11个采空区的塌陷程度进行判别,评价结果准确合理。研究结果表明:该模型避免了以往研究中的赋权争议问题,克服了样本量不足致使模型无法应用的问题,而且能够应用更多的赋权方法识别排序的稳定程度,体现出样本间的分层信息。     

基于集对模型的地下工程塌方风险分析方法

为度量和监控地下工程塌方风险态势,提出一种基于集对模型的地下工程塌方风险分析方法。通过归纳地下工程塌方灾害因素,建立地下工程塌方风险的层次化结构,应用变异系数法确定风险指标的权重值;以集对分析(SPA)的同异反联系度和距离测度为基础,构建地下工程塌方风险态势监控机制及分析模型。给出地下工程塌方风险态势度量工作步骤,确定地下工程塌方灾害风险集对势、贴近度和次序关系。最后,通过对塌方风险分析样本的集对计算,为有效防范塌方灾害由潜伏性向灾变性转化提供防范重点。     

基于尺寸效应的采空区危险度RS-TOPSIS法辨识

为准确预测地下采空区危险性,选用采空区结构的跨度、暴露面积、高度、埋深、矿柱尺寸布置等5个采空区危险度结构尺寸影响因素作为评价指标,建立采空区危险度粗糙集-逼近理想解排序法(RS-TOPSIS)综合评价体系。基于粗糙集理论(RS)中的粗糙依赖度,通过计算评价指标与评价等级间的粗糙依赖度得到指标权重。以40个采空区探测系统(CMS)实测采空区作为评价对象,根据单指标分类区间下限构造5个不同等级的典型采空区,结合逼近理想解的排序法(TOPSIS),实现采空区危险度5级贴近度的分类,并辨识实测采空区危险度。研究结果表明,用为采空区群矿山建立的采空区危险度基于结构尺寸效应的RS-TOPSIS法,能够实现危险度5级分类辨识,辨识结果与采空区危险度数值分析结果吻合度为92.5%。     

集对分析法在尾矿坝稳定性安全评价中的应用

本文运用相关性分析,将与尾矿坝稳定有关的参数和设计指标进行分类,建立了相互独立指标的尾矿坝稳定性评价指标体系,并应用集对理论建立了尾矿坝稳定性评价模型。随后通过国内尾矿库专家系统对体系各指标进行的评估,结合层次分析法,得到了各指标的权重;根据集对分析法,并将指标分成3个级别,由于归一化联系数μ的取值范围[-1,1],按照"均分原则",从而提出尾矿库运行期稳定等级的划分方法。最后,应用尾矿坝稳定性评价模型对某尾矿坝稳定性进行计算分析,实例分析表明,本文建立的尾矿坝稳定性评价指标体系和安全评价模型,可以用于评估尾矿库运行期稳定性的状况。     

基于SPA-VFRM的城市要害系统综合应急能力研究

为反映城市要害系统综合应急能力的发展现状及过程,在分析城市要害设施系统构成与面临的主要灾害类型基础上,提出从充分性、精确性、抵御性和及时性4个维度评价应急能力的思路,建立城市要害系统综合应急能力评估指标体系,并应用层次分析法与变异系数法确定指标综合权重,结合集对分析（SPA）与可变模糊识别模型（VFRM）构建城市要害系统综合应急能力的评价模型;运用该模型实证分析某市要害系统综合应急能力发展现状。实证表明:该市要害系统综合应急能力呈现“波浪式升高”的动态发展趋势,灾害抵御能力是构成综合应急能力的主要方面;3种方法的评价结果排序基本一致,表明该模型的评估结果稳健、可靠,能够有效反映城市要害系统综合应急能力发展情况。     

城市轨道交通车站应急疏散方案决策研究

城市轨道交通应急疏散方案决策是1个多准则决策问题,传统方法难以将决策者的偏好与风险倾向纳入考虑,因此引入累积前景理论与集对分析,得到1种结合累积前景理论与集对分析的决策方法。该方法考虑决策者面对风险时的态度,计算出方案的累积前景值;引入集对分析,通过时间权重与准则权重将前景值与集对势联系起来,计算出方案综合集对势,并利用其大小对备选方案进行排序;最后通过实例计算以及对权重的扰动分析,验证了方法有效性。     

环境质量的模糊综合评判—灰色关联分析

本文简要分析了环境质量评价中目前广泛应用的各种评价方法与模型。在此基础上提出环境质量综合评判－灰色关联优势分析复合模型，应用于黄山风景区景观生态环境质量的综合评价，取得了满意的结果。     

Modelling algal blooms in the Dutch coastal waters by integrated numerical and fuzzy cellular automata approaches

In this paper, an integrated numerical and fuzzy cellular automata model was developed to predict possible algal blooms in Dutch coastal waters basing on the irradiance, nutrients and neighbourhood conditions. The numerical module used Delft3D-WAQ to compute the abiotic conditions, and fuzzy cellular automata approach was applied to predict the algal biomass that was indicated by chlorophyll a concentration. The simulated results of year 1995 were compared with that from BLOOM II model, and the advantages, disadvantages as well as future improvement were presented. In general, through this study, it is seen that the integrated modelling deserves more research inputs because: (1) the hydrodynamic processes and nutrients concentrations can be simulated in details by numerical method; (2) the irregular and sparse water quality and biological data, and the empirical knowledge from experts can be explored by the fuzzy logic technique; (3) the spatial heterogeneity, local interactions and the emerge of patchiness could be well captured through the cellular automata paradigm.     

Assessment of herbaceous plant habitats in water-constrained environments: predicting indirect effects with fuzzy logic

Herbaceous plant production plays a key role in determining the function of rangeland ecosystems in the semi-arid and Mediterranean regions. Therefore, assessment of herbaceous plant habitats is important for understanding the ecosystem functioning in these regions and for applied purposes, such as range management and land evaluation. This paper presents a model to assess herbaceous plant habitats in a basaltic stony environment in a Mediterranean region. The model is based on geographic information systems (GIS), remote sensing and fuzzy logic, while four indirect variables, which represent major characteristics of herbaceous habitats, are modeled: rock cover fraction; wetness index (WI); soil depth; and slope orientation (aspect). A linear unmixing model was used to measure rock cover on a per pixel basis using a Landsat TM summer image. The wetness index and local aspect were determined from digital elevation data with 25 m × 25 m pixel resolution, while soil data were gathered in a field survey. The modeling approach adopted here is process-based and assumes that water availability plays a crucial role in determining herbaceous plant production in Mediterranean and semi-arid environments. The model rules are based on fuzzy logic and are written based on the hypothesized water requirements of the herbaceous vegetation. The results show that on a polygon basis there is positive agreement between the model proposed here and previous mapping of the herbaceous habitats carried out in the field using traditional methods. Intrapolygon tests show that the use of a continuous raster data model and fuzzy logic principles provide an added value to traditional mapping. Moreover, herbaceous biomass measurements at two time intervals—mid- and peak winter season—corresponded with the habitat assessment predictions achieved using a new scenario that is proposed in this research. This scenario suggests that rockiness increases herbaceous production on south-facing slopes, while in other slope aspects the rock cover has lower impact on herbaceous growth. Due to its simplicity, the model suggested here can be used by planners and managers, to adjust range activities over large areas. The process-based approach should allow adaptation of the model to other regions more effectively than models that were formulated on a purely empirical basis. The model could also be used to study the relationship between water availability and ecosystem productivity on a regional scale.