论空间数据挖掘和知识发现的理论与方法

首先分析了空间数据挖掘和知识发现(SDMKD)的内涵和外延;然后分别研究了用于SDMKD的概率论、证据理论、空间统计学、规则归纳、聚类分析、空间分析、模糊集、云理论、粗集、神经网络、遗传算法、可视化、决策树、空间在线数据挖掘等理论和方法及其进展;最后展望了SDMKD的发展前景。     

北京高科技产业集群衍生效应及其影响分析——基于中关村科技园区的案例研究

以北京高科技产业集群衍生效应的分析为核心,将衍生效应分为两大类:企业衍生效应和技术衍生效应.通过实证研究.分析出衍生效应的主要表现形式,并以此为基础设定分析标准,用以反映北京高科技产业集群的发展特点.研究发现:衍生效应能够提升竞争优势和智力资源的利用效率,对高科技产业集群的发展有积极意义;同时,衍生效应能够强化集群专业化分工,促进技术扩散;技术衍生效应能促进企业规模化和专业化,而企业衍生效应强化了集群内部的竞争,能促进技术创新和研发投入.     

Simulations of realistic granular soils in oedometer tests using physics engine

Discrete element method (DEM) has become a preeminent numerical tool for investigating the mechanical behavior of granular soils. However, traditional DEM uses sphere clusters to approximate realistic particles, which is computationally demanding when simulating many particles. This paper demonstrates the potential of using a physics engine technique to simulate realistic particles. The physics engines are originally developed for video games for simulating physical and mechanical processes that occur in the real world to produce realistic game experiences. The simulation accuracy and efficiency of physics engines have been significantly improved in the last two decades allowing them to be used as a scientific tool in many disciplines. This paper introduces modeling methodologies of physics engine including realistic particle representation and the contact model. Then, oedometer tests are simulated using realistic particles scanned by X-ray computed tomography (X-ray CT). The simulation results agree well with experimental results. This paper demonstrates that physics engines can output contact parameters for geotechnical analysis and force chains for visualization.     

太阳高层大气物质交换的热机效应——色球-日冕过渡区模型

我们认为存在于太阳高层大气中的一种稳定的物质交换,可以起到冷却日冕和加热色球一日冕过渡区的热机作用。还考虑到来自日冕的热传导和过渡区的辐射损失,计算了太阳过渡区的温度、密度和速度分布。并对物质流通量及速度边值与太阳过渡区厚度之间的关系作了讨论。     

Why are sustainable practices often elusive? The role of information flow in the management of networked human-environment interactions

Analyzing the spatial and temporal properties of information flow with a multi-century perspective could illuminate the sustainability of human resource-use strategies. This paper uses historical and archaeological datasets to assess how spatial, temporal, cognitive, and cultural limitations impact the generation and flow of information about ecosystems within past societies, and thus lead to tradeoffs in sustainable practices. While it is well understood that conflicting priorities can inhibit successful outcomes, case studies from Eastern Polynesia, the North Atlantic, and the American Southwest suggest that imperfect information can also be a major impediment to sustainability. We formally develop a conceptual model of Environmental Information Flow and Perception (EnIFPe) to examine the scale of information flow to a society and the quality of the information needed to promote sustainable coupled natural-human systems. In our case studies, we assess key aspects of information flow by focusing on food web relationships and nutrient flows in socio-ecological systems, as well as the life cycles, population dynamics, and seasonal rhythms of organisms, the patterns and timing of species’ migration, and the trajectories of human-induced environmental change. We argue that the spatial and temporal dimensions of human environments shape society’s ability to wield information, while acknowledging that varied cultural factors also focus a society’s ability to act on such information. Our analyses demonstrate the analytical importance of completed experiments from the past, and their utility for contemporary debates concerning managing imperfect information and addressing conflicting priorities in modern environmental management and resource use.     

数字地形分析方法研究的维度——精准、高效、易用

数字地形分析基于数字高程模型计算各种地形信息,在诸多地理现象和地理过程的定量刻画和模拟中都发挥着不可或缺的重要作用。作为地理信息空间分析的一个基本组成内容、GIS的必备功能之一,数字地形分析的方法研究不断深化、扩展。本文从一个新的视角,即方法研究的维度,对该领域已有工作及发展趋势进行梳理,将数字地形分析方法研究工作归纳为依次显现出的3个研究维度：① 精准,即如何设计新的数字地形分析方法以更准确、精确地计算出符合地理学认知、满足应用领域问题求解所需的地形信息;② 高效,即如何使数字地形分析的计算更高效;③ 易用,即如何使数字地形分析对于应用者（尤其是相关应用领域中非数字地形分析专家的用户）更易用。特别是近年新显现出的“易用”研究维度,通过研究设计数字地形分析领域应用建模知识的形式化表达及相应的推理应用方法,有望实现数字地形分析应用工作流的智能化构建,满足实际应用中对数字地形分析的易用性需求;同时,其研究思路和方法也可为地理信息空间分析中诸多其他分支领域解决所面临的类似问题提供借鉴。     

Reference data enhancement for geographic information retrieval using linked data

Gazetteers are instrumental in recognizing place names in documents such as Web pages, news, and social media messages. However, creating and maintaining gazetteers is still a complex task. Even though some online gazetteers provide rich sets of geographic names in planetary scale (e.g. GeoNames), other sources must be used to recognize references to urban locations, such as street names, neighborhood names or landmarks. We propose integrating Linked Data sources to create a gazetteer that combines a broad coverage of places with urban detail, including content on geographic and semantic relationships involving places, their multiple names and related non‐geographic entities. Our final goal is to expand the possibilities for recognizing, disambiguating and filtering references to places in texts for geographic information retrieval (GIR) and related applications. The resulting ontological gazetteer, named LoG (Linked OntoGazetteer), is accessible through Web services by applications and research initiatives on GIR, text processing, named entity recognition and others. The gazetteer currently contains over 13 million places, 140 million attributes and relationships, and 4.5 million non‐geographic entities. Data sources include GeoNames, Freebase, DBPedia and LinkedGeoData, which is based on OpenStreetMap data. An analysis on how these datasets overlap and complement one another is also presented.     

空间知识地图信息传输模型的研究

空间知识地图是提取和传输空间知识的工具,已得到了广泛的应用。从地图信息传输论的角度出发,本文提出了空间知识地图的传输模型和传输效率的改进方向,对提升空间知识地图的应用效率有一定的指导意义。     

Extracting and analyzing semantic relatedness between cities using news articles

News articles capture a variety of topics about our society. They reflect not only the socioeconomic activities that happened in our physical world, but also some of the cultures, human interests, and public concerns that exist only in the perceptions of people. Cities are frequently mentioned in news articles, and two or more cities may co-occur in the same article. Such co-occurrence often suggests certain relatedness between the mentioned cities, and the relatedness may be under different topics depending on the contents of the news articles. We consider the relatedness under different topics as semantic relatedness. By reading news articles, one can grasp the general semantic relatedness between cities; yet, given hundreds of thousands of news articles, it is very difficult, if not impossible, for anyone to manually read them. This paper proposes a computational framework which can ‘read’ a large number of news articles and extract the semantic relatedness between cities. This framework is based on a natural language processing model and employs a machine learning process to identify the main topics of news articles. We describe the overall structure of this framework and its individual modules, and then apply it to an experimental dataset with more than 500,000 news articles covering the top 100 US cities spanning a 10-year period. We perform exploratory visualizations of the extracted semantic relatedness under different topics and over multiple years. We also analyze the impact of geographic distance on semantic relatedness and find varied distance decay effects. The proposed framework can be used to support large-scale content analysis in city network research.     

地理知识的形式化

地理知识形式化是地理专家系统中的瓶颈问题，本文探讨了地理知识形式化的基础、地理圈层与地理系统分解为因子层数据的可能性、圈层与系统之间的公因子、地理数据与地理知识的相互转化、地理知识的等级与分等定级、地理知识的编码等问题。