滑坡预测与风险评价专家系统

滑坡是一种常见的地质灾害，其预测过程十分复杂。文章介绍一个滑坡预测与风险评价专家系统ＬＦＥＥＳ。ＬＦＥＥＳ对滑坡的预测分为定性预测和定量预测两大类：定性预测以专家经验知识为基础，由符号推理产生定性的预测结；定量预测则由定量计算模型产生定量的预测结论。ＬＦＥＥＳ能够根据预测结论对滑坡灾害进行风险评价，并给出防治策略。讨论ＬＦＥＥＳ的总体结构、知识表示、推理方法和定量计算模型，并对ＬＦＥＥＳ用于滑坡多发城市重庆及其附近地区的几个典型滑坡的实现情况和预测结果进行了详细介绍。     

基于灰色关联分析和案例推理的边坡稳定性评价方法

采用基于案例推理的方法 (CBR)来评价边坡稳定性 ,并利用灰色关联理论 ,提出基于灰色关联分析的案例检索方法 ,应用于边坡工程实例 ,效果良好 ,且将实例应用结果与同等条件下欧式距离的检索结果比较 ,说明此方法合理有效、具有明显的优越性     

空间方向关系粗糙推理

针对现有的空间方向关系表达模型不能捕获其所固有的不精确性和模糊性这一缺点，把粗糙集理论和方法引入方向关系的表达，提出了方向关系粗糙表达方法、变精度粗糙表达方法以及方向关系的粗糙推理方法，以加强对不精确性和模糊性的处理和分析能力，并能够把模糊对象和精确对象之间的方向关系统一到一个框架中来描述。     

Indicator Pattern Combination for Mineral Resource Potential Mapping with the General C-F Model

As an uncertain reasoning model, the general C-F model was originally developed for processing the uncertainties of rule-based knowledge in the field of artificial intelligence. In this model, certainty factors and combined certainty factors are defined and used for expressing the strengths of knowledge rules and knowledge rule combinations, respectively. The certainty factor can reflect the believable degree of inferring hypothesis on the basis of a proof. Similarly, the combined certainty factor can reflect the believable degree of inferring hypothesis on the basis of the proof combination. It is a function of the related certainty factors and can be determined through combining the certainty factors via the combining rule of the general C-F model. In this paper, the general C-F model has been successfully applied to mineral resource potential mapping. We call this model as the applied form of the general C-F model. In this applied form, the certainty factor is applied to expressing the believable degree of inferring mineral occurrence on the basis of one of the map pattern states associated with the mineral occurrence. Correspondingly, the combined certainty factor is applied to expressing the believable degree of inferring the mineral occurrence on the basis of the map pattern state association. And it is also applied to expressing mineral resource potentials in the mineral resource potential mapping. In the current form, the first step in implementing the general C-F model is to estimate a pair of certainty factors for each map pattern under combination. The next step is to determine the combined certainty factor for the map pattern states coexisting in each locality of the mapping area. The last step is to generate the combined-certainty-factor raster map or the combined-certainty-factor contour map in order to select mineral resource targets. The applied form of the general C-F model is demonstrated on a case study to select mineral resource targets. The experimental results manifest that the model can be compared with the weights-of-evidence model in the effectiveness of mineral resource target selection.     

基于实例类比推理的边坡稳定性评价方法

基于工程实例,利用边坡工程经验、类比推理原理,建立基于实例类比推理的边坡稳定性评价方法。文中基于工程经验,提出了一种新的归一化效用函数,将不同量纲的原始评估指标值转换到[-1,1]区间,同时尽可能地将指标值转换成效益型指标,使其更好地体现“奖优罚劣”。还定义了一种新的实例类比推理计算方法,使其能更好地体现实例之间的距离与差异。实例分析结果说明,所提出的方法不仅有效,而且简单实用。     

人文地理学研究方法述要

人文地理学是地理学的重要分支学科，20世纪60年代在人文地理学领域内进行的计量革命引发了人们对地理学的理论建设以及地理学方法论 思考，但是计量革命从一开始就经历着种种责难，文章从对计量革命这一运动的观察开始，对人文地理学方法论进行了反思，在此基础上对当前人文地理学采用的方法进行概括总结，并对一些研究方法应用前景予以展望。     

空间方向关系的反转运算

反转运算作为空间方向关系最为基础的一种运算,目前对其研究还没有达到形式化和系统化的要求。这里以空间方向关系的集合表示为基础,在严格定义方向关系的前提下,从点状目标间方向关系的反转运算出发,分类研究了各种矩形主方向关系的反转运算规则,对两目标出现重合区域的方向关系进行了重点研究,给出了运算结果并予以证明。     

地震预报的科学哲学与方法论探索——50年回眸与前瞻

地震预报是具高度复杂性的世界科学难题。以我国50余年实践中的问题为导向,以其揭示的自然现象为依托,从科学哲学及方法论视角,回顾经验归纳、还原论动力学、归纳-演绎和复杂动力系统等方法。通过汶川、唐山等震例探讨认识论因素在预测预报中的重要作用。进入地球系统科学新时期,建议以大陆变形复杂动力系统演化及其地震行为、经验与数值预测桥梁的图像（斑图）动力学作为地震预报的自然观和方法论。它们虽不完善,但更贴近大自然的整体性、进化性和非线性本质,又能包容连接多种思路与方法;既具前瞻性,又具可操作性;地震具可预测性,又具预测的不完全确定性;预测→预报→减轻灾害尚存在颇大的可创新空间。     

基于案例推理的统计地图表示方法智能选取中的应用

地图符号的选择在空间信息可视化中至关重要。本文基于案例推理的研究范式和专题制图过程,提出了一种智能化专题制图的CBR框架,它依赖的知识主要是系统所存储的专题地图设计过程中解决问题的具体记录。本文从案例库内容设计、案例表达和数据库模式、案例相似性计算和案例检索等方面重点研究了CBR在统计地图表示方法智能选取中的应用,并以《中国人口地图集》为蓝本,以myCBR为工具,展现了CBR在专题地图设计知识获取、表达和推理中的应用潜力。     

基于典型事例推理的路径规划方法研究(英文)

Case-based reasoning is an AI technique in which the previous solutions are stored for future use. People are used to guiding themselves according to those routes that are stored in their memories and have been used by them before. It is just based on people’s preference to familiar routes, which are gained through the study of the cognitive activities. We propose to apply the intelligent method based on the case reasoning to path planning. It is impossible for a case base to store all the solutions to all the shortest paths; therefore, part of them should be stored. However, which routes should be stored and which should not be? How do we adapt the cases that have already been stored and how do we acquire the shortest route based on them? All these issues need to be explained by integrating knowledge of the network on account of case-based reasoning techniques. This paper suggests the case-based reasoning in another point. This means finding some irreplaceable links on the basis of the complete analysis of the problems space, which are called the must_be_passed link between the source and destination. Merely compute the shortest path case from those best exit/entry nodes of the grids to the irreplaceable links, and then add them into the case base storing for future use. This method is based on case-based reasoning technique and completely considers the properties of the problem space. In addition to the use of knowledge of the natural grid in the route network, this method is more efficient than existing algorithms on computing efficiency.