新型智能化互感器校验仪的研究与实现

通过分析互感器比、角差测量方法,提出并实现了一种基于精密90°锁相移相电路的新型智能化互感器校验仪自动化测量方案。     

工程建设项目的多测整合对策研究

以广州市开展联合测绘的改革成效为基础,进一步探索研究工程建设项目审批服务全链条中的测绘服务事项,重点关注优化测绘服务流程、统一测绘技术标准规范、强化对测绘成果的共享互认以及完善测绘行业管理制度等内容,通过优化测绘服务体系为审批制度改革"加速",为优化营商环境"助力",为全国各地全面推出"多测合一"改革提供可复制推广的经...     

中国石化枯竭气藏型储气库注采技术及发展建议

经长输管线输送的天然气注入到地下空间而形成的人工气藏称为地下储气库。国内外现有储气库大多数是枯竭气藏型地下储气库。中国石化储气库建设起步较晚,基础较为薄弱,同时与国内外已建成储气库相比,中石化储气库建设面临的地质条件和注采工况也较为复杂。以中国在建最大储气库项目中原文23储气库为例,其复杂地质条件以及面临的"快瞬变非稳态增压"注采难题需要进行专门研究。分析了目前中石化枯竭型气藏储气库建库现状,提出了建库技术挑战,总结了现阶段取得的注采关键技术研究成果,通过分析中国石化枯竭气藏型储气库注采技术研究现状和最新进展,提出了国产化技术完善、智能化注采营运、一体化模拟实验室的建设等方面的发展建议和要求,为持续加强规模化储气库群建设的支持提供参考。     

规范基层国土资源工作流程的几点想法

针对当前国土资源所规范化建设中出现的科室业务衔接过程中的种种问题,就如何明确科所责权、完善机制,全面提升科所业务水平,提出了"一对一"业务指导、通过"收(退)件登记卡"完善管理机制、制定不同行政许可事项工作程序流程图等措施。     

基于A-star算法的矿井事故救援研究

针对井下不同形状巷道几何空间特征,确立以空间点、线、面为基本图元,以巷道中心线作为三维模型构建的基础框架,建立巷道三维模型。采用启发式路径搜索A-star算法,实现了应急救援路线智能快速选择。实践证明,该方法对于矿井事故定位和救援具有一定的实用性。     

The Disparate Neighborhood Impacts of the Great Recession: Evidence from Chicago

Abstract

We advance scholarship about how macroeconomic forces differentially manifest themselves across local spaces by developing a holistic conceptual framework and empirical analyses involving multilevel change modeling. Unlike prior work, we examine differential rates of change in neighborhood indicators. We illustrate our approach with Chicago data measuring the crime, housing, and economic domains of neighborhood quality of life over the 2000–2009 period. We find that the local dynamic manifestations of macroeconomic cycles were far more nuanced than have been previously observed. Neighborhood indicators moved along distinct trajectories, sometimes but not necessarily tracking each other or the overall business cycle, and they changed with varied intensities. The Great Recession of 2006–2009 had disparate negative impacts on lower-income and minority-occupied neighborhoods' local job opportunities, home prices, and home foreclosures, though this was not true for credit or crime indicators. Credit indicators performed geographically much differently than in the prior Chicago recession.     

Positional uncertainty in manually digitized map data

Digital map coordinates represent the locations of real world entities. As such, differences can exist between the ‘tru’ and digital database coordinates of those entities. This paper reports on a statistical characterization of positional error in manually-digitized and map-registered point data, the relative contribution of point type and operator to digitization error, and the effects of map media type on the positional uncertainty associated with registration.

Manually-digitized point data were collected by four operators from mylar and paper maps. Point locations for a number of different feature types were sampled from United States Geological Survey (USGS) 1:24 000 scale maps. Linear models were used to estimate the variance components due to among-operator, map media, point type and registration effects. The statistical distribution of signed distance deviations for manually-digitized data was leptokurtic relative to a random normal variate. Unsigned deviations averaged 0-054 mm. Squared distance deviations were not different from a Chi-square random variate. Variance components indicate that among-operator differences in positional uncertainty were large and statistically significant, while differences among point type were small and non-significant. Signed distance deviations associated with a first-order afhne followed a normal distribution. Unsigned distance deviations associated with a first-order affinc transformation averaged 0068mm, and squared distance deviations were distributed as a Chi-square. Differences in transformation accuracy were not related to type of map media.     

An improved ant colony optimization (I-ACO) method for the quasi travelling salesman problem (Quasi-TSP)

Traveling salesman problem (TSP) and its quasi problem (Quasi-TSP) are typical problems in path optimization, and ant colony optimization (ACO) algorithm is considered as an effective way to solve TSP. However, when the problems come to high dimensions, the classic algorithm works with low efficiency and accuracy, and usually cannot obtain an ideal solution. To overcome the shortcoming of the classic algorithm, this paper proposes an improved ant colony optimization (I-ACO) algorithm which combines swarm intelligence with local search to improve the efficiency and accuracy of the algorithm. Experiments are carried out to verify the availability and analyze the performance of I-ACO algorithm, which cites a Quasi-TSP based on a practical problem in a tourist area. The results illustrate the higher accuracy and efficiency of the I-ACO algorithm to solve Quasi-TSP, comparing with greedy algorithm, simulated annealing, classic ant colony algorithm and particle swarm optimization algorithm, and prove that the I-ACO algorithm is a positive effective way to tackle Quasi-TSP.