集值系统的辨识、控制及应用

本文总结了近年来关于集值系统的研究工作:在辨识方面,从不同的系统结构、不同的噪声情况和不同的集值情形等方面进行了深入的研究,针对性地提出了参数解耦、比例满秩输入设计、联合可辨识、经验分布函数、递推投影辨识等有效的辨识方法,得到了一系列重要结果;在适应控制方面,都实现了一类集值增益系统的适应跟踪控制;在同步控制方面,提出了双时间尺度同步算法和递推投影同步算法,实现了二值量测下的多个体同步控制;在应用方面,分别将集值辨识应用到复杂疾病建模和雷达目标识别问题中,构造了新的、更为有效的统计验证方法,在低信噪比下将识别率提高了10%.     

Research on radar emitter attribute recognition method

In order to solve emitter recognition problems in a practical reconnaissance environment, attribute mathematics is introduced. The basic concepts and theory of attribute set and attribute measure are described in detail. A new attribute recognition method based on attribute measure is presented in this paper. Application example is given, which demonstrates this new method is accurate and effective. Moreover, computer simulation for recognizing the emitter purpose is selected, and compared with classical statistical pattern recognition through simulation. The excellent experimental results demonstrate that this is a brand-new attribute recognition method as compared to existing statistical pattern recognition techniques.     

Comparative tempo‐spatial pattern analysis: CTSPA

A new method is illustrated for describing the characteristics of urban pattern changes over different time periods. This method employs vector geometry, paired centroids, shared boundary lines, and overlain polygons. Three new statistics are proposed for characterizing local polygon feature changes in quantity, shape, and size. These statistics are standardized, based on conventional theories from urban geography such as directional concentric zones and user‐designated corridors to document both regional and global patterns of land‐use change. This method is used to analyse land‐use changes in metropolitan Detroit between 1990 and 2000. The Detroit case study indicates that the CTSPA statistics are effective in describing urban spatial pattern changes and in characterizing the evolution of discrete urban landscapes over selected periods.     

Discovering relative motion patterns in groups of moving point objects

Technological advances in position‐aware devices are leading to a wealth of data documenting motion. The integration of spatio‐temporal data‐mining techniques in GIScience is an important research field to overcome the limitations of static Geographic Information Systems with respect to the emerging volumes of data describing dynamics. This paper presents a generic geographic knowledge discovery approach for exploring the motion of moving point objects, the prime modelling construct to represent GPS tracked animals, people, or vehicles. The approach is based on the concept of geospatial lifelines and presents a formalism for describing different types of lifeline patterns that are generalizable for many application domains. Such lifeline patterns allow the identification and quantification of remarkable individual motion behaviour, events of distinct group motion behaviour, so as to relate the motion of individuals to groups. An application prototype featuring novel data‐mining algorithms has been implemented and tested with two case studies: tracked soccer players and data points representing political entities moving in an abstract ideological space. In both case studies, a set of non‐trivial and meaningful motion patterns could be identified, for instance highlighting the characteristic ‘offside trap’ behaviour in the first case and identifying trendsetting districts anticipating a political transformation in the latter case.     

Mapping urban fingerprints of odonyms automatically extracted from French novels

ABSTRACT

In this paper, we propose and discuss a methodology to map the spatial fingerprints of novels and authors based on all of the named urban roads (i.e., odonyms) extracted from novels. We present several ways to explore Parisian space and fictional landscapes by interactively and simultaneously browsing geographical space and literary text. Our project involves building a platform capable of retrieving, mapping and analyzing the occurrences of named urban roads in novels in which the action occurs wholly or partly in Paris. This platform will be used in several areas, such as cultural tourism, urban research, and literary analysis. The paper focuses on extracting named urban roads and mapping the results for a sample of 31 novels published between 1800 and 1914. Two approaches to the annotation of odonyms are compared. First, we describe a proof of concept using queries made via the TXM textual analysis platform. Then, we describe an automatic process using a natural language processing (NLP) method. Additionally, we mention how the geosemantic information annotated from the text (e.g., a structure combining verbs, spatial relations, named entities, adjectives and adverbs) can be used to automatically characterize the semantic content associated with named urban roads.     

一种基于方向检测的等高线分离方法

提出了一种地形图上等高线分离方法,方法建立在基于方向检测的线宽识别算法基础上,使等高线分离具有很强的宽度敏感性,同时由于在线宽识别过程中考虑了等高线的空间连续性,方法具有很好的分离效果.实践证明,算法可以为等高线进一步矢量化提供高质量的底图,减少等高线自动矢量化的后续编辑工作量,具有很强的实际意义和理论价值.     

多级模糊模式识别模型在地质环境质量评价中的应用

应用多级模糊模式识别模型进行地质环境质量评价,克服了最大隶属度原则所不适用的地方,而且以相对隶属度、隶属函数为基础理论,使隶属度、隶属函数的计算更容易.建立环境质量评价模型,并应用于陕西省略阳县地质环境质量综合评价中,应用结果表明,该方法合理、可行.     

LAMOST观测控制系统体系结构设计

由于大天区面积多目标光纤光谱天文望远镜(LAMOST)系统非常复杂,系统研制的时间比较长,系统建成后有相当长的使用年限,就要求观测控制系统(OCS)有足够长的生命周期(使用、维护及升级),可扩展性和良好的可维护性,因此系统需要一个合理健全、内在一致的体系结构。根据OCS的建模和体系结构的概念,在对OCS建模及参考各种体系结构模式的基础上完成了基于构件的层状的OCS系统体系构架,融合了MVC,代理等体系结构模式。详细讨论了OCS体系结构的静态模型和动态模型,并在OCS的1级系统实现了此体系结构。     

多传感器数据融合技术与应用

研究了多传感器数据融合理论的相关算法及其在多传感器系统中的应用，分析了数据融合技术目前在应用方面存在的问题；针对应用证据理论（D-S方法）解决多传感器条件下的数据融合过程中存在的失效问题，给出了修正合成规则；通过实例对其进行了验证。     

基于DP算法的槽线自动判识

槽线自动识别是天气图自动化分析的重要内容,但目前的气象槽线分析主要通过人工实现。为了能够实现槽线准确快速的自动提取,本文从等压线数据着手,提出了一种基于Douglas-Peucker算法的气象槽线自动识别方法。该方法通过Douglas-Peucker算法从等压线中提取曲线特征点作为槽点,充分保留了等压线曲线的主要特征和拓扑关系;依据由等压线拓扑结构设定的规则连接槽点构成候选曲线,进行槽脊线区分得到槽线识别结果。试验表明该方法能够实现槽线的自动分析,分析结果较为准确。