Development of a data mining method for land control

Land resources are facing crises of being misused, especially for an intersection area between town and country, and land control has to be enforced. This paper presents a development of data mining method for land control. A vector-match method for the prerequisite of data mining i. e., data cleaning is proposed, which deals with both character and numeric data via vectorizing character-string and matching number. A minimal decision algorithm of rough set is used to discover the knowledge hidden in the data warehouse. In order to monitor land use dynamically and accurately, it is suggested to set up a real-time land control system based on GPS, digital photogrammetry and online data mining. Finally, the means is applied in the intersection area between town and country of Wuhan city, and a set of knowledge about land control is discovered.     

Managing expert-information uncertainties for assessing collapse susceptibility of abandoned underground structures

Assessing the collapse susceptibility of abandoned cavities at a regional scale is associated with large uncertainties that are mainly related to the very nature of the phenomena, but also to the difficulty in collecting exhaustive information at such a scale on often “forgotten” structures. In this context, the expert's role is essential, because he is able to synthesize the information resulting from the inventory and from the commonly imprecise, if not vague, criteria on the basis of his experience and his knowledge of the geological, historical, economic regional context.In this article, we propose mathematical tools for representing and processing this information in order to give flexibility to this step and manage the uncertainty inherent in the expert's information. The first tool, based on the weight of evidence theory, is for managing the uncertainty due to the heterogeneous spatial distribution of the data, whereas the second tool, based on the fuzzy set theory, is for managing the imprecision and incompleteness of available data, which hinder the definition of the class boundaries of the quantitative decision criteria. Based on an appropriate representation of the uncertainty sources (related to the input data and to the expert diagnostic), we then propose a methodology that integrates the uncertainty in the final output of the collapse susceptibility assessment and provides a confidence indicator useful within the decision-making process. The proposed methodology is applied to the Arras territory in the North of France, where abandoned chalk pits (dating back to the Roman ages) and war saps located in the vicinity of the First World War front lines (i.e. covered trenches), raise both difficulties for urban planning.     

集对分析径向基函数神经网络预测模型

将集对分析与径向基函数神经网络结合,提出了集对分析径向基函数神经网络预测模型。模型思路是将研究对象t-1时和t时的影响因子集构造为集对并计算联系度,由联系度的同一度、差异度、对立度及研究对象t-1时的值为输入,研究对象t时的值为输出,构建径向基函数神经网络。以年径流预测为例研究表明,模型结构清晰、步骤明确、预测精度较高,为集对分析应用于水文预测提供了新思路。     

偏序向量空间中集值映射的一类扩张定理

经典的Hahn-Banach扩张定理及其推广定理有着非常广泛的应用,但主要都是讨论单值映射的扩张性质。为了进一步讨论多值映射的扩张性质,通过构造的方法,利用了zorn引理及偏序向量空间的完备性,得到了当定义域空间是一个实向量空间,而值域空间是由锥引入序的Dedekind完备的偏序向量空间时集值映射的一类扩张性质,以及当给值域空间引入相应拓扑时连续集值映射的一类扩张性质。其结果进一步推广了Hahn-Banach扩张定理,扩大了其应用范围。     

基于集对分析的膨胀土胀缩性Vague集评价模型

膨胀土胀缩性等级评价是膨胀土地区工程治理中的首要问题。本文探讨了基于集对分析的膨胀土胀缩性等级评价模型,以克服膨胀土胀缩性评价指标的不确定性和复杂性。模型以Vague集描述膨胀土胀缩性等级的确定性和不确定性,并应用集对分析构造Vague集的隶属函数。通过实例应用及与其他方法评价结果的对比分析,表明该模型应用于膨胀土胀缩性等级评价是有效可行的,且具有判断结果准确、易于操作等优点。     

三维叠后地震数据可纵向显示的处理方法

在三维地震资料处理中,为使叠后相邻测线的地震数据在绘图纸上能够纵向同时显示,达到节约绘图纸、降低成本的目的,本文提出了一种利用地震资料处理模块生成可纵向显示的三维地震绘图数据的处理方法.该方法通过进行叠后三维数据体的分离、延长测线数据的记录长度、修改线号和数据体舍并等处理工作,产生可纵向显示的绘图数据体.经实际绘图显示,不同测线的地震剖面由原来的横向单张显示,转为了纵向的多张绘图.因此,大大节约了纸张,降低了地震资料处理的成本.     

基于FCM算法的粗糙集理论在边坡稳定性影响因素敏感性分析中的应用

结合粗糙集理论与模糊C-均值（FCM）算法,提出一种边坡稳定性影响因素敏感性分析新方法。将边坡稳定性影响因素敏感性分析问题转化为粗糙集理论中的属性重要性评价问题,采用FCM算法离散连续属性数据,给出敏感性分析的具体算法。以圆弧型破坏边坡为例,对影响边坡稳定性的单因素与多因素敏感性进行分析,证明了该方法的可行性和有效性。     

Environmental decision-making under uncertainty using intuitionistic fuzzy analytic hierarchy process (IF-AHP)

Analytic hierarchy process (AHP) is a utility theory based decision-making technique, which works on a premise that the decision-making of complex problems can be handled by structuring them into simple and comprehensible hierarchical structures. However, AHP involves human subjective evaluation, which introduces vagueness that necessitates the use of decision-making under uncertainty. The vagueness is commonly handled through fuzzy sets theory, by assigning degree of membership. But, the environmental decision-making problem becomes more involved if there is an uncertainty in assigning the membership function (or degree of belief) to fuzzy pairwise comparisons, which is referred to as ambiguity (non-specificity). In this paper, the concept of intuitionistic fuzzy set is applied to AHP, called IF-AHP to handle both vagueness and ambiguity related uncertainties in the environmental decision-making process. The proposed IF-AHP methodology is demonstrated with an illustrative example to select best drilling fluid (mud) for drilling operations under multiple environmental criteria.     

基于集对分析的滑坡变形动态建模研究

滑坡是一个确定-不确定的动态系统,其变形表现出复杂的非线性演化特征。为了克服传统分析方法在处理系统不确定性方面的不足,将集对分析法（SPA）引入岩土变形监测分析领域,并结合层次分析法（AHP）提出了滑坡变形动态预测模型,给出了基于概率论的最优预测算法,提出并证明了集对论中最大同一度在等势条件下存在极限解,据此提出位移势的概念。在位移势的基础上,进行SPA二次建模,提出了基于SPA的滑坡变形与水库蓄水过程相关性动态分析模型。运用上述预测模型对新近发生的刘家沱滑坡进行变形监测定量分析,实践证明：最优预测值具有良好的短期预报精度;位移势能够表征系统当前状态下位移所能达到的最大潜力,可作为短期预测的上限值,其变化能够反映系统宏观层面上的演化特征,对滑坡演变加速预警具有指导意义;运用集对分析方法进行滑坡变形响应滞后效应的定量研究是一条可行的新思路,反演结果与实际情况吻合;该方法在岩土监测分析领域有良好的应用前景。