城市精细化管理大数据应用模型研究

该文以无锡市智慧城管大数据应用实践为例,介绍了无锡市城市管理局围绕城市精细化管理实际工作的需要,针对城市动态运行管理、精细化网格管理和行业应用管理等方面的重点、热点、难点问题,综合运用大数据理念和技术,构建城市精细化管理大数据应用场景,建立大数据应用模型,打造“用数据说话、用数据决策、用数据管理、用数据创新”的智慧化城市管理模式,实现大数据应用场景化落地的一些主要思路和做法。

基于存储过程的高性能数据库应用模型研究

基于C/S及B/S的传统数据库应用模型在处理海量数据时,系统通常会对许多无用数据进行运算,增加了运算的时间复杂度和空间复杂度。针对这个问题,提出了一种基于存储过程的高性能数据库应用模型,仅仅对有效数据进行运算,减少了对大量无用数据的运算,提高了SQL的运行速度,同时也降低了网络数据流量。实践结果表明,该存储过程数据库模型比传统数据库处理模型的处理效率提高了n倍。

基于CORBA/Java的Web数据库应用模型研究

讨论了解决跨平台可移植的Web数据库应用问题常用的理论模型;提出了由传统模型到基于CORBA和Java的模型的转变方法;设计了具有跨平台性、可移植性、安全性等性能的基于CORBA/Java的多层次Web数据库应用新模型,并分析了其工作原理和性能特点.

城市综合管理大数据赋能应用模型研究--苏州市城市综合管理服务平台的实践与思考

本文以苏州市城市管理数据赋能应用实践为例,聚焦城市管理精细化、科学化、智能化,综合运用大数据理念和技术,构建数据赋能应用场景,旨在打造“大数据+城市管理”新模式的一些主要新思路。

矿产资源潜力评价数据模型应用支持研究

全国矿产资源潜力评价数据模型,是全国矿产资源潜力评价项目的基础。它描述了该工作重要中间成果数据和最终成果数据本身及其关系,入库数据格式的规范化以及入库数据内容的标准化检查均离不开数据模型的支持。因此如何使该数据模型支持应用,是一个需要研究的重要问题。文中以解决这一问题为出发点,以如何依照数据模型新建一个图件为例,研究如何用数据字典技术,解决相关的模型应用问题。

一种基于XML的Web数据库应用模型研究及应用

通过对传统数据库应用模型局限性的分析 ,提出了一种基于 XML 的具有简单实用性的 Web数据库应用模型。

时空大数据及其应用

首先从哲学时空观、国家管理和社会治理的时空观、作战指挥和军事行动的时空观、非线性复杂地理世界科学表达的时空观和大数据本质的时空观5个方面分析了时空大数据的理论依据,论述了时空大数据的内涵、构成和特征。在此基础上,给出了时空大数据应用的基础平台--时空大数据平台的内涵和功能,着重从内涵、功能、关键技术、采用标准、技术架构、服务共享特点及发展趋势等方面,综合分析比较了现行基于网络服务空间信息共享与空间数据互操作、基于网格服务的信息资源共享与协同工作和基于云计算的地理信息服务3种服务模式各自的特点。提出了基于“网格集成”与“弹性云”相结合的时空大数据平台的技术体制、关键技术及“共用时空大数据平台+”的应用概念模型,讨论了时空大数据平台在数字中国建设与数字经济发展及国家一体化算力网工程中的作用。

智慧校园数据应用快速构建平台的设计与实现

本文设计并实现了基于数据应用模型和共享组件的数据应用快速构建平台,以现有数据为基础,快速构建数据应用。解决数据分析过程中涉及的无系统关系数据采集和管理困难,数据分析结果展示和使用方式单一等问题。与智慧校园中已有的数据采集和分析平台一起,加快数据赋能业务进程,满足智慧校园中不断增长的数据分析需求。

基于数据挖掘的电子政务综述

本文主要介绍了电子政务及数据挖掘在电子政务中的应用模型。

广东天气雷达覆盖现状的评估

利用广东省10部天气雷达2010—2016年的观测基数据,对雷达的国土覆盖、地形遮挡现状进行评估,结果表明:珠三角地区覆盖密集,大部分区域覆盖都达到4～5部雷达重叠,海岸线连续性覆盖良好;粤东地区覆盖均匀,大部地区覆盖达到3～4部雷达重叠;粤西部覆盖较好,大部分地区达到2～3部雷达覆盖重叠;粤北等人口较少的地区雷达覆盖差、遮挡严重。

An equivalent-tool theory for acoustic logging and applications

The influence of an acoustic logging tool on borehole guided wave propagation should be considered in the processing and inversion of the guided waves for formation acoustic property estimation. This study introduces an equivalent-tool theory that models the tool response using an elastic rod with an effective modulus and applies the theory to multipole acoustic logging for both wireline and logging while drilling （LWD） conditions. The theory can be derived by matching the tool’s acoustic impedance/conductance to that of the multipole acoustic wavefield around the tool, assuming that tool radius is small compared to wavelength. We have validated the effectiveness and accuracy of the theory using numerical modeling and its practicality using field data. In field data applications, one can calibrate the tool parameters by fitting the theoretical dispersion curve to field data without having to consider the actual tool’s structure and composition. We use a dispersion correction example to demonstrate an application of the simple theory to field data processing and the validity of the processing result.

Deposit 3D modeling and application

By the aid of the international mining software SURPAC, a geologic database for a multi-metal mine was established, 3D models of the surface, geologic fault, ore body, cavity and the underground openings were built, and the volume of the cavity of the mine based on the cavity 3D model was calculated. In order to compute the reserves, a grade block model was built and each metal element grade was estimated using Ordinary Kriging. Then, the reserve of each metal element and every sublevel of the mine was worked out. Finally, the calculated result of each metal reserve to its actual prospecting reserve was compared, and the results show that they are all almost equal to each other. The absolute errors of Sn, Pb, and Zn reserves are only 1.45%, 1.59% and 1.62%, respectively. Obviously, the built models are reliable and the calculated results of reserves are correct. They can be used to assist the geologic and mining engineers of the mine to do research work of reserves estimation, mining design, plan making and so on.

Variable damping constraint tomography and its application in VSP Data

First arrival travel time tomography has achieved wide application. However, tomographic resolution is insufficient because geometry constraints cause rays to be unevenly distributed in the velocity model. The variable damping constraint method adopts uneven priori information to match uneven data distribution which can lessen the correlation between velocity correction values and ray coverage density. In this paper, we combine the variable damping constraint with a smoothness constraint which is added into the regularization equations in velocity inversion to avoid instability caused by only using the variable damping constraint method. The alpha-trimmed-mean filter is used to smooth and denoise intermediate results in the velocity inversion process. We use the LSQR algorithm to enhance the convergence rate and suppress error propagation in solving linear equations. In this paper, we apply the proposed tomographic method to perform velocity inversion using VSP data. The application in recovery test of the checkerboard model and velocity inversion of real VSP data show that the variable damping constraint method can improve tomographic quality because it can solve the effects of uneven ray coverage. In addition, the examples show that the tomographic result near geophones is much more reliable than other areas in the velocity model.

Study of S-wave ray elastic impedance for identifying lithology and fluid

In this paper, we derive an approximation of the SS-wave reflection coefficient and the expression of S-wave ray elastic impedance （SREI） in terms of the ray parameter. The SREI can be expressed by the S-wave incidence angle or P-wave reflection angle, referred to as SREIS and SREIP, respectively. Our study using elastic models derived from real log measurements shows that SREIP has better capability for lithology and fluid discrimination than SREIS and conventional S-wave elastic impedance （SEI）. We evaluate the SREIP feasibility using 25 groups of samples from Castagna and Smith （1994）. Each sample group is constructed by using shale, brine-sand, and gas-sand. Theoretical evaluation also indicates that SRE1P at large incident angles is more sensitive to fluid than conventional fluid indicators. Real seismic data application also shows that SRE1P at large angles calculated using P-wave and S-wave impedance can efficiently characterize tight gas-sand.

Usage of 3D Point Cloud Data in BIM （Building Information Modelling）： Current Applications and Challenges

BIM （building information modelling） has gained wider acceptance in the A/E/C （architecture/engineering/construction） industry in the US and internationally. This paper presents current industry approaches of implementing 3D point cloud data in BIM and VDC （virtual design and construction） applications during various stages of a project life cycle and the challenges associated with processing the huge amount of 3D point cloud data. Conversion from discrete 3D point cloud raster data to geometric/vector BIM data remains to be a labor-intensive process. The needs for intelligent geometric feature detection/reconstruction algorithms for automated point cloud processing and issues related to data management are discussed. This paper also presents an innovative approach for integrating 3D point cloud data with BIM to efficiently augment built environment design, construction and management.

Application of Extreme Value Theory to Generation and Analysis of Pseudorandom Samples

The article deals with the methodology of pseudorandom data analysis. As a mathematical tool for carrying out the research the extreme value theory was used that creates one of the directions in mathematical statistics, and is related to investigating the extreme deviations from the median values in probability distributions. Also, the methods for estimating unknown parameters and algorithm of random-number generation are discussed. The models of treatment the extreme values are constructed which are based on machine generated sample and approach is proposed for their future application for constructing forecasting models.

Research on the Applications of Probability Model and Matrix Transformation in Data Analysis and Management under the Environment of Information Time

In this paper, we research the probability theory and matrix transformation based technique to manage the data for processing and analysis. Clustering analysis research has a long history, over the decades, the importance and the cross characteristics with other research direction to get the affirmation of the people. The probability theory and linear algebra act as the powerful tool for analyzing and mining data. The experimental result illustrates the effectiveness. In the near future, we plan to conduct more theoretical analysis on the topic.

Research and application of flood detention modeling for ponds and small reservoirs based on remote sensing data

This paper proposes a method of small reservoir flood detention modeling that utilizes data from the American land resources satellite Landsat TM/ETM+. Precipitation and potential evapotranspiration are taken as the control conditions in this method on the basis of basin terrain classification. The objective of this method is to solve the question of a small-scale water conservancy project’s influence on flood forecasting precision, which can be used in the basin with multitudinous small reservoirs in the upstream region and can help estimate non-runoff data for small reservoir runoff. Taking the 20060826 flood as an example, the flood detention quantity of 19 small reservoirs is modeled. The results show that the absolute error of the total flood detention quantity is 0.2×10 4 m 3 , and the relative error is 0.12%. The flood detention quantity of small reservoirs in the entire basin is then modeled using this method, and the primary flood forecasting model is adjusted. After adjustment, the precision is significantly improved, with the relative error decreasing from 31.8% to 10.1%.

A Web-based Geographic Hypermedia System:Data Model,System Design and Prototype Applications

Geographic Hypermedia(GH)is a rich and interactive map document with geo-tagged graphics,sound and video ele-ments.A Geographic Hypermedia System(GHS)is designed to manage,query,display and explore GH resources.Recognizing emerging geo-tagged videos and measurable images as valuable geographic data resources,this paper aims to design a web-based GHS using web mapping,geoprocessing,video streaming and XMLHTTP services.The concept,data model,system design and implementation of this GHS are discussed in detail.Geo-tagged videos are modeled as temporal,spatial and metadata entities such as video clip,video path and frame-based descriptions.Similarly,geo-tagged stereo video and derived data are modeled as interre-lated entities:original video,rectified video,stereo video,video path,frame-based description and measurable image(rectified and disparity image with baseline,interior and exterior parameters).The entity data are organized into video files,GIS layers with linear referencing and XML documents for web publishing.These data can be integrated in HTML pages or used as Rich Internet Appli-cations(RIA)using standard web technologies such as the AJAX,ASP.NET and RIA frameworks.An SOA-based GHS is designed using four types of web services:ArcGIS Server 9.3 web mapping and geoprocessing services,Flash FMS 3.0 video streaming ser-vices and GeoRSS XMLHTTP services.GHS applications in road facility management and campus hypermapping indicate that the GH data models and technical solutions introduced in this paper are useful and flexible enough for wider deployment as a GHS.

Weighted quantile regression for longitudinal data using empirical likelihood

This paper proposes a new weighted quantile regression model for longitudinal data with weights chosen by empirical likelihood(EL). This approach efficiently incorporates the information from the conditional quantile restrictions to account for within-subject correlations. The resulted estimate is computationally simple and has good performance under modest or high within-subject correlation. The efficiency gain is quantified theoretically and illustrated via simulation and a real data application.