GPS在石化管线测量三维控制网建立中的应用与分析

文章介绍了上海某石化厂厂区间石化管线三维坐标测量首级控制网（GPS平面控制网、精密水准高程控制网）的建立及数据处理方法，对比分析与讨论了对基点进行严格筛选的必要性，为保证GPS网的精度对基准点进行了检核，并对三维控制网的稳定度进行了评定。     

Visualizing the relationship between geographic and social media network space

This research explores the relationship between geographic and social media network space. The purpose of this paper is twofold: to perform a geo-enhanced network analysis and to create an example social media network using a select location identified in the study area as important in the results of the geo-enhanced network analysis. A straightforward, non-technical example is provided to the readers on how location data and social media network data can be overlaid to visualize potential local firm to firm and firm to customer connections in geographic and social media network space. An example of how to identify these potential connections locally through social media networks using Twitter is demonstrated. By considering the geographic location in network structures, it is possible to convey the role distance plays in discerning prospective local social media marketing partners, and also track the spread of information flow through social media networks.

     

中国水文站网

简要回顾了中国水文站网和观测技术的发展过程。根据2005年全国水文站网普查数据,分析了中国水文站网测报自动化水平和水文站网密度与布局现状,结合500km2以上河流水文站网设立情况调查,客观评价了水文站网对江河的水文控制程度。在评估中,与有关国家情况做了对比,以进一步认识中国水文站网现况。     

典型降水预报ANN多指标优选——以太湖湖西区为例

为提高多种典型人工神经网络应用于降水预报的精度与稳定性并做出优选,对太湖流域湖西区丹徒、丹阳、金坛、溧阳、宜兴5站的年降水量时间序列建立基于组成成分分析的人工神经网络模型,并通过平均相对误差、平均绝对误差、均方根误差及合格率4项评价指标对比分析预报效果。该模型采用Mann-Kendall法、秩和检验法、谱分析法进行组成成分分析;建立BP网络、小波神经网络、RBF网络、GRNN网络及Elman网络模拟并预测随机成分,与确定性成分叠加得年降水量预报结果。在湖西区的研究结果表明,基于组成成分分析的人工神经网络模型的拟合及预测精度高于原始人工神经网络和线性自回归模型,GRNN网络的预测精度与稳定性高于其他4类神经网络。     

Modeling of the Shale Volume in the Hendijan Oil Field Using Seismic Attributes and Artificial Neural Networks

Petrophysical properties have played an important and definitive role in the study of oil and gas reservoirs, necessitating that diverse kinds of information are used to infer these properties. In this study, the seismic data related to the Hendijan oil field were utilised, along with the available logs of 7 wells of this field, in order to use the extracted relationships between seismic attributes and the values of the shale volume in the wells to estimate the shale volume in wells intervals. After the overall survey of data, a seismic line was selected and seismic inversion methods (model-based, band limited and sparse spike inversion) were applied to it. Amongst all of these techniques, the model-based method presented the better results. By using seismic attributes and artificial neural networks, the shale volume was then estimated using three types of neural networks, namely the probabilistic neural network (PNN), multi-layer feed-forward network (MLFN) and radial basic function network (RBFN).     

基于重置神经网络在油气储层预测方面的应用

神经网络在地质、油气储层方面有着极其广泛的应用,但是神经网络的结构不仅直接影响到网络性能的优劣,而且较大的影响了其现实应用的效果。这里尝试着将与重置算法相结合的BP神经网络应用于油气储层预测方面,并证实重置神经网络具有更好的应用前景和现实意义。     

Spatial loyalty and territorial embeddedness in the multi-sector clustering of the Berguedà region in Catalonia (Spain)

The development of clusters of local growth is supported by different processes. Endogenous economic development produced by small and medium-sized enterprises (SMEs) is based on family firms in which local market characteristics influence the sectorial diversification that emerges within certain regions. In the Berguedà region (Catalonia, Spain), the formation of a successful network of SMEs in three main sectors (food, textile and machinery) in the 1990s demonstrated the importance of grass-roots prerequisites, including industrial tradition, social networks and a sense of spatial loyalty, one of the main concepts studied in this paper. The aim of this paper is to study how institutions, local economic networks and collective social agents generate a propitious economic space that constitutes favourable embedding in Berguedà. However, the key element in this industrial system is the loyalty that entrepreneurs and workers feel towards their industrial region. These two processes, territorial embeddedness and spatial loyalty, appear to be two of the major forces behind the economic dynamism of the region and have led to the formation of a new cluster of firms.     

Network configurations and R&D activities of the ICT industry in Suzhou municipality, China

This paper analyzes the network structure and R&D activities of the information and communication technology (ICT) industry in Suzhou municipality, known previously for its local state-directed Sunan model of development. Suzhou, however, has been undergoing dramatic restructuring to remake itself into a globalizing production center. We highlight the significance of the Chinese state and local/regional assets in shaping the trajectories of globalization and regional development, and the increasing importance of domestic markets and regional clusters/agglomeration for foreign ventures. We have found that Suzhou’s development path, heavily dependent on external forces, has made Suzhou a TNC (transnational corporation) satellite district. We also find that the ICT industry in Suzhou has a dual-structure, segmented between foreign-invested enterprises (FIEs) and domestic firms. TNCs tend to network among themselves and their interfirm networks are increasingly domestic and regionally embedded in the Yangtze River Delta, while the linkages between TNCs and local firms are weak. We argue that there is a series of technological, structural, spatial, and institutional “mismatches” that limits the establishment of “global pipelines” of knowledge exchange. We hold that the nature of global-local networks is contingent upon regional endogenous capacities and the specific ways in which global capital interacts with local institutions. Therefore, perspectives on TNCs’ local embeddedness must be positioned in their regional/external networks. We also analyze the constraints placed on Suzhou’s development into an innovative city and promote the integration of global and local/regional assets through development of indigenous capacities.     

人工神经网络模型在地学研究中的应用进展

近年来,随着人工神经网络（ANNs）自身技术的不断完善,应用ANNs模型成功解决各类地学问题的案例大量出现。通过对其发展历程进行分析发现,20世纪80年代末国际地学分析中已开始融入ANNs技术,国内则滞后 1～2年。在地学分析中使用的各类人工神经网络类型中,BP模型应用最广,占到85％以上。在10余年的应用过程中,虽然地学的各个分支学科都移植了一种或数种ANNs模型作为其分析工具,但水文、地质、大气、遥感等领域应用较为广泛。传统地学定量分析中的单变量或多变量预测成为人工神经网络地学模型的主要应用客体。同时,诸如模式识别和过程模拟等也是ANNs模型求解的对象。目前,随着建模经验和知识的积累,地学ANNs模型的发展呈现出多种技术综合集成的态势,遗传算法、小波转换、模拟退火算法以及模糊逻辑等方法与ANNs模型融合,成为解决地学分析中非线性问题的利器。     

Power and influence tactics in the promotion of regional development: An empirical analysis of the work of Finnish regional development officers

Increased complexity and rapid pace of change demand more from people responsible for regional development at various levels of activity. This paper has its roots in a belief that the more complex situations are, the more regional development is dependent on the leadership and network management capacity of key individuals. Studying more deeply the roles that various individuals, and the coalitions formed by them, have in institutionalisation, deinstitutionalisation and reinstitutionalisation processes might provide us with additional analytical leverage in regional development studies. This paper focuses on diffuse networks of dispersed powers from a Finnish regional development officer’s point of view. Regional development officers are those people whose job it is to boost the economic development of their respective regions in Finland.The research questions discussed here are: (a) What kind of power is exercised by Finnish regional development officers; and (b) how do regional development officers aim to gain influence for their efforts to promote regional development? The empirical research is based on data gathered (a) through 41 interviews with Finnish actors responsible for the promotion of economic development in city governments, technology centres, regional development agencies, and ministries and other national bodies, and (b) through internet survey of development officers at local, regional and national levels (531 respondents, response rate 51.8%). The survey was designed to solicit information about power and influence tactics in the context of regional development. The empirical analysis shows, for example, how interpretive power and network power are more important for regional development officers than institutional and resource power, and how indirect influence tactics surpass direct tactics.     

浅析GIS通信本地网管理系统的建设

通信本地网是我国公用通信网的重要组成部分, 其管理工作以往一直是由人工完成的.要做好通信本地网的管理与维护工作, 必须采用先进的技术建立GIS通信本地网管理系统, 实现电信公司通信本地网的规划设计、工程施工、运行维护管理与统计分析等的计算机化, 为各相关部门提供多专业、多层次、多目标的综合服务.详细介绍了通信本地网管理的现状, 从基于管理、人员、电信发展以及新技术的发展等方面进行分析, 阐述了建立GIS通信本地网管理系统的必要性, 详细介绍了在建设系统时需要考虑的各种技术问题: 系统设计原则、系统应该遵照的标准、涵盖的资源、系统主要功能、数据管理模式、数据库选型、硬件选型和GIS平台的选择等.还介绍了基于MAPGIS平台开发的通信网络地理信息系统在全国的应用情况.      

对数字测绘数据传输的网络安全与数据文件自动更新的思考

本文结合实例介绍了数字测绘科学数据在局域网与互联网上的网络安全问题,包括加密、传输、防病毒、防黑以及局域网内基于数据存储服务器的数据文件自动备份更新的方法.     

Modeling soil collapse by artificial neural networks

The feasibility of using neural networks to model the complex relationship between soil parameters, loading conditions, and the collapse potential is investigated in this paper. A back propagation neural network process was used in this study. The neural network was trained using experimental data. The experimental program involved the assessment of the collapse potential using the one-dimensional oedometer apparatus. To cover the broadest possible scope of data, a total of eight types of soils were selected covering a wide range of gradation. Various conditions of water content, unit weights and applied pressures were imposed on the soils. For each placement condition, three samples were prepared and tested with the measured collapse potential values averaged to obtain a representative data point. This resulted in 414 collapse tests with 138 average test values, which were divided into two groups. Group I, consisting of 82 data points, was used to train the neural networks for a specific paradigm. Training was carried out until the mean sum squared error (MSSE) was minimized. The model consisting of eight hidden nodes and six variables was the most successful. These variables were: soil coefficient of uniformity, initial water content, compaction unit weight, applied pressure at wetting, percent sand and percent clay. Once the neural networks have been deemed fully trained its accuracy in predicting collapse potential was tested using group II of the experimental data. The model was further validated using information available in the literature. The data used in both the testing and validation phases were not included in the training phase. The results proved that neural networks are very efficient in assessing the complex behavior of collapsible soils using minimal processing of data. This revised version was published online in July 2006 with corrections to the Cover Date.     

青藏及华北阵列式区域大地电磁场标准观测网建设方法与实验

大地电磁参数标准网的建设需要大量第一手的观测资料,观测资料的质量直接决定了标准网的可靠性。本文分析了大地电磁测深仪器设备、资料采集与处理技术,确定了青藏及华北阵列式区域大地电磁场标准观测网的建设方法;在此基础上,在山东菏泽地区对11535和11635号标准点进行了野外观测试验,对采集的宽频及长周期数据进行了深入处理,形成的对辅助测站和中心测站布置、数据采集时间、资料处理手段和远参考测站布设等要求,将指导青藏及华北阵列式区域大地电磁场标准网的建设,并对中国大陆其他区域大地电磁场标准网建设具有一定参考意义。     

Transnational elites in global cities: British expatriates in Singapore's financial district

Skilled international migration is as an important process of both contemporary globalization and the global city. The establishment of a transnational elite of expatriate labour in international finance plays a vital part in the accumulation of capital within international financial centres (IFCs). Expatriate labour has become a major determinant of the IFC, creating financial capital through complex social relations, knowledge networks, practices and discourses. The principal argument being made in this paper is that expatriates are major agents in the accumulation and transfer of financial knowledge in the IFC, and that such processes are undertaken through expatriate global–local knowledge networks and other social practices. The paper is divided into three major parts. Following a discussion of transnational elites as expatriates in global cities, which also conceptualises their contribution to the spatialization of financial knowledge networks, the empirical study investigates the working, social and cultural knowledge networks and practices of British expatriates in Singapore. Finally, the paper revisits the conceptual work on transnational elites and suggests that expatriates were deeply embedded in global–local relations in the workplace and the business/social sphere through interaction with local ‘western educated/experienced' Singaporeans, but were disembedded from the local in the home and other household social spaces due to the invisibility of the local population in their interactions. Both the theoretical and empirical analyses suggests that expatriates are flow in the Castellian spatial logic of the network society.     

基于遗忘因子的BP神经网络水文实时预报方法

在应用神经网络进行洪水预报时,因洪水系统随着河道上游来流、区间降雨、河床演变等因素的动态变化,其特性并不总是按照基本相同的规律变化,对这类系统的参数辨识,要求算法具有较强的实时跟踪能力,以适应模拟或预测洪水运动变化过程的要求。在BP神经网络模型的基础上,运用最小二乘递推算法,引入时变遗忘因子实时跟踪模型中时变参数的变化,建立了神经网络在非线性系统中动态系统输入、输出数据间的映射关系。计算实例表明:该法对参数的快速时变具有较快的跟踪能力和较高的辨识精度,是一种非常实用的水文实时预报方法。     

国内外城市生态网络建设经验及对上海的启示

城市基本生态网络的实施是一项艰巨的任务,必须在行政、经济、技术等多方面进行保障,并在政策方面有所创新,才能激发政府、开发商、业主及其他利益相关者等对实施生态空间的积极性。本文搜集和分析了国内外生态城市建设、生态控制线实施等相关案例以及生态补偿机制的研究和实践,提出了对上海市实施生态控制线的建议。     

A neural network approach to geostatistical simulation

Neural networks offer a non-algorithmic approach to geostatistical simulation with the possibility of automatic recognition of correlation structure. The paper gives a brief overview of neural networks and describes a feedforward, back-propagation network for geostatistical simulation. The operation of the network is illustrated with two simple one-dimensional examples which can be followed through with hand calculations to give an insight into the operation of the network. The convergence of the network is described in terms of the variogram calculated from the values at each of the output nodes at each iteration.     

西太平洋地区数字地震台网建设及其有关工作

地震科学某种意义上是一门观测科学。没有精确、可靠的地震观测资料,地震预报及相关的地球科学研究就缺乏基础。目前,越来越多的国家,尤其是主要的多地震国家都在大力发展大动态、宽频带、高精度的数字地震观测台网。西太平洋很多国家也正在计划加强或建立新的数字地震台网。本综述根据1998年西太平洋地球物理会议《地震台网》专题会议的上交流的论文,介绍了该地区数字地震台网的建设及其某些应用的概况。     

内蒙古呼和浩特市承压地下水水位监测网优化

定量评价地下水监测网的合理性对于准确、经济地获取高质量的监测数据尤为重要。本文针对呼和浩特市平原区现行承压水监测网, 以估计误差标准差作为衡量监测网合理与否的特征参数, 借助ArcGIS地学统计模块, 利用普通Kriging插值模型, 对待测点进行插值, 获取估计误差标准差等值线图。结果表明: 监测水位估计误差标准差范围由优化前的0.47~4.44变为优化后的0.5~0.8(除研究区西南边界附近外), 研究区整体估计误差标准差显著减小, 且全区范围内变幅较小。优化后的监测网在满足监测精度需要的同时, 能够较大程度节省监测网的运行费用。研究成果为呼和浩特市平原区承压水水位监测提供一个较优化的监测网布设方案, 进而为研究区承压地下水的合理开发利用以及相关环境地质问题提供真实可靠的数据支撑, 具有重要的应用价值。