A Bayesian network approach for predicting seismic liquefaction based on interpretive structural modeling

The Bayesian network (BN) is a type of graphical network based on probabilistic inference that has been gradually applied to assessment of seismic liquefaction potential. However, how to construct a robust BN remains underexplored in this field. This paper aims to present an efficient hybrid approach combining domain knowledge and data to construct a BN that facilitates the integration of multiple factors and the quantification of uncertainties within a network model to assess seismic liquefaction. Initially, only using given domain knowledge, a naive network model can be constructed using interpretive structural modeling. Thereafter, some effective information about the naive model is provided to construct a robust model using structural learning of BN from historic data. Finally, the returning predictive results and the predictive results are compared to other methods including non-probabilistic and probabilistic models for seismic liquefaction using the metrics of the overall accuracy, the area under the curve of receiver operating characteristic, prediction, recall and F₁ score. The methodology proposed in this paper achieved better performance, and we discussed the power and value of the proposed approach at the end of this paper, which suggest that BN is a good alternative tool for seismic liquefaction prediction.     

An object-oriented knowledge representation structure for exploration data integration

Knowledge representation structure and reasoning processes are very important issues in the knowledge-based approach of integrating multiple spatial data sets for resource exploration. An object-oriented knowledge representation structure and corresponding reasoning processes are formulated and tested in this research on the knowledge-based approach of integrating spatial exploration data. The map-based prototype expert system developed in this study has self-contained knowledge representation structure and inference mechanisms. It is important to distinguish between lack of information and information providing negative evidence for a map-based system because the spatial distribution of data sets are uneven in most cases. Error and uncertainty estimation is also an important component of any production expert system. The uncertainty propagation mechanisms developed here work well for this type of integrated exploration problem. Evidential bellef function theory provides a natural theoretical basis for representing and integrating spatially uneven geophysical and geological information. The prototype system is tested using real mineral exploration data sets from the Snow Lake area, northern Manitoba, Canada. The test results outline the favorable exploration areas successfully and show the effectiveness of the knowledge representation structure and inference mechanisms for the knowledge-based approach.     

《地图学》多元教学方法改革与实践

针对测绘工程专业传统的《地图学》课程教学中存在的只注重理论教学、教材内容陈旧、缺乏贴近学生实际和当前测绘科技发展的问题,该文提出《地图学》的多元教学方法,即将教书育人理念融入课堂教学、现代教学手段融入传统课堂及书本理论教学融入实践体验的教学方法。     

从受训神经-模糊模型中提取知识

本文对用于模式分类、函数逼近、参数估计的多层感知器 (MLPs)给出 1个清晰的关于内部行为的解释。作者以单隐层的 MLP为例 ,论述了关于 MLP的内部行为的半线性分析理论。对受训的MLP,将隐层单元的输出分别定义为网络输出的正、负“内部分量”;定义内部分量的连接权重集为给定问题的“内部判别模式”;建立了 MLP和模糊集相结合的新模型 ;分析了 MLP的结构为 N- 2 - 1和N- H- 1 ,给出权重初始化的方法 ;提出了 1种从受训神经 -模糊模型 (NFMs)中提取知识的全新的具有实用价值的方法。     

浅析大数据对测绘保障的影响

通过对大数据时代的特点进行分析,结合实际从测绘保障的方式、职能、方法等方面进行剖析,总结了大数据时代测绘保障的重点,目的是探索大数据时代测绘保障的新方向,为提高测绘保障服务奠定基础。     

Knowledge based systems for risk assessment of the subsurface of contaminated sites

Computer-based risk evaluation methods are practical tools to compare automatically and evaluate contaminated sites. HYDRISK is an example of adequate knowledge-based systems: HYDRISK evaluates hydrogeological properties and chemical criteria relevant to contaminant transport with respect to the necessary remedial actions. It works at a high investigative level and enables geologists and engineers to draw differentiated conclusions for selecting remediation methods for the contaminated site. HYDRISK emphasizes space and time dependent aspects of the contaminant transport. It is supported by a geographic information system (GIS) to display the evaluation results. Some ideas on considering the spatiotemporal variability of relevant parameters by means of geostatistical methods and numerical models will be given.     

Looking for the critical geographer, or why bodies and geographies matter to the emergence of critical geographies of Latin America

This paper argues that critical geographies of Latin America begin with an analysis of how and why the bodies and geographies of geographers themselves matter. To focus on the geographer as a producer of knowledge is not to advocate the kind of navel gazing so abhorrent to many scholars. Rather, it is an effort to call attention to and critically assess how the geographer's embodied social position and geographic location inform the production of knowledge about and representations of Latin American people and nature. To illustrate how and why bodies and geographies matter, I draw from feminist and post-colonial theory and include examples from my own experiences and those of other researchers doing fieldwork in Latin American countries. I conclude by exploring the notion of situated knowledge as a tactic that writes bodies and geographies into academic texts. Ultimately, situating knowledge represents a political intervention and contribution to the broader goals of emancipatory politics shared by critical human geographers.     

如何开展地震现场科普宣传工作初探

地震科普宣传工作多是在地震发生之前开展,主要偏重的是如何地震避险。地震灾害发生后对灾区民众如何有效地减轻地震灾害及合理地配合外来救援力量的科普宣传缺乏系统性。本文从地震现场科普宣传的形式、内容及如何更好地实现现场科普宣传三个方面对地震现场科普宣传工作进行分析,旨在为利用地震现场科普宣传维护震区的社会稳定、减轻灾害损失及顺利地开展地震现场救援提出建议。     

矿床统计预测单元划分的方法与程序

在矿床统计预测中,如何确定最佳的统计预测单元,目前尚无通用的准则和算法,它的划分往往取决于地质学家对研究区控矿条件的认识,矿化的实际分布殂态及统计预测所采用的评价模型等多种因素。系统功能齐全,基本上满足了资源评价的各种需求,实现了预测单元划分的自动化和智能化。