高阶地球重力场模型的评价及其优选

采用"移去-恢复"技术确定大地水准面,需要一个全球重力场模型作为参考场。本文采用基于模糊集合理论的最大隶属度原则,通过某试验区的33个GPS水准点的实测大地水准面差距与模型大地水准面差距的比较分析,从国际重力场服务提供的EGM96、EIGEN-CG01C、EIGEN-CG03C、GFZ93A、GFZ96、OSU91A、PGM2000A等七个高阶全球重力场模型中,选择OSU91A作为该地区最优的参考重力场模型。     

基于空间数据挖掘的煤矿安全管理的研究

煤炭企业属于传统的资源开采型企业,煤矿安全对煤炭企业影响巨大,安全工作在煤矿生产中占有重要地位。其管理好坏直接关系到煤炭企业的生存和发展。煤矿安全管理任务十分艰巨,是因为影响煤矿安全的因素非常复杂,而且含有大量的不确定性因素。本论文利用空间数据挖掘技术来研究采煤方式的选择,并选用焦作矿务局某矿一工作面的实例进行分析,结果表明用粗集来确定采煤方式是比较客观的、科学的和全面的,对保证煤矿的安全提供了一定的保障。     

四面体格网模型的三维拓扑关系计算

四面体格网(TEN)模型是一种重要的空间数据构模方法,侧重于三维空间对象内部的表达,但是存在着数据量大、计算速度慢的问题。三维拓扑关系是三维GIS的重要研究内容,为此,该文提出了面向TEN的三维拓扑关系计算方法。基于点集拓扑学理论,将TEN分解为内部、边界和外部3个集合,并使用9交模型描述了TEN/TEN的8种拓扑关系;设计了面向TEN的三维拓扑关系计算流程,详细阐述了面向TEN的三维拓扑关系计算的核心算法;基于提出的三维拓扑关系算法,设计了面向TEN的拓扑关系计算实验。实验结果表明:该文提出的面向TEN的三维拓扑关系计算方法,能够满足TEN之间拓扑关系计算的需求。     

Deriving a minimum set of viewpoints for maximum coverage over any given digital elevation model data

This paper introduces how to automatically derive a minimum set of viewpoints for maximum coverage over a large scale of digital terrain data. This is a typical data and computation-intensive research covering a series of geocomputation tasks that have not been implemented efficiently or optimally in prior works. This paper introduces a three-step computational solution to resolve the problem. For any given digital elevation model (DEM) data, automatic generation of control viewpoints is the first step through map algebra calculation and hydrological modeling approaches. For each viewpoint, the viewshed calculation then has to be implemented. The combined viewshed derived from the viewshed of all viewpoints establishes the maximum viewshed coverage of the given DEM. Finally, detecting the minimum set of viewpoints for the maximum coverage is a Non-deterministic Polynomial-time hard problem. The outcome of the computation has broader societal impacts since the research questions and solutions can be adapted into real-world application and decision-making practice, such as the distribution, optimization and management of telecommunication infrastructure and wildfire observation towers, and military tactics and operations dependent upon landscape and terrain features.     

一种优化的最少换乘公交算法

针对当前算法存在可能遗漏最佳邻近站点或距离偏大和效率偏低等问题,文章基于换乘次数最少的原则,提出了一种优化的公交换乘算法:在起讫点处邻近距离设定方面做出改进,将起点处的邻近距离设定为用户可接受的最大步行距离,同时使讫点处的邻近距离动态变化;将传统的一个起点对应一个讫点的搜索模式,改进为一个起点对应多个讫点的搜索模式;引入两个阈值对搜索过程进行控制,且通过对大量的实验数据进行统计分析得到两个阈值的最优值。实验结果表明该算法能有效提高路线的实用性并降低搜索时间。     

利用改进粒子群算法的关联规则挖掘

针对传统的关联规则挖掘方法需要耗费大量时间来产生频繁项的问题,该文设计了一种引入负反馈机制的改进粒子群算法。该算法采用负反馈机制,在粒子位置更新前通过判断粒子是否将落入恶劣区域,较好地避免了粒子更新过程中对无用频繁项的重复计算,从而有效减少了数据库的扫描次数。通过挖掘土地覆盖类型与地形特征的空间关联关系,结果表明:所提算法不仅可以提高空间关联规则的挖掘效率,还可以发现仅具有高置信度的易被忽视关联规则。该研究结果对空间关联分析、同位模式挖掘等具有一定的参考价值。     

Subfossil Chironomidae (Insecta: Diptera) along a latitudinal gradient in Finland: development of a new temperature inference model

Numerical techniques were used to study chironomid distribution and abundance in lakes from a 1000 km transect in Finland, with special interest on the effect of local summer air temperatures on chironomid assemblages. The final aim of the study was to develop a chironomid‐based palaeotemperature inference model. The dataset consisted of 82 lakes (of which 77 were used in the model after deletion of outliers), with catchments spanning from boreal coniferous forests to mountain birch woodland and tundra vegetation. Numerical analysis showed that the mean July air temperature was the most significant variable explaining the distribution and abundance of chironomids in Finnish lakes. Weighted‐averaging partial least squares techniques were used to develop a palaeotemperature inference model for mean July air temperature reconstructions. The model performance statistics were favourable, with cross‐validated coefficient of determination (r²) of 0.78, root mean squared error of prediction of 0.721°C and maximum bias of 0.794°C. Based on these values, the transfer function is a valid means of performing quantitative palaeotemperature estimates in downcore studies. Copyright © 2008 John Wiley & Sons, Ltd.     

Assessment of CHADFDM satellite-based input dataset for the groundwater recharge estimation in arid and data scarce regions

Aquifer natural recharge estimations are a prerequisite for understanding hydrologic systems and sustainable water resources management. As meteorological data series collection is difficult in arid and semiarid areas, satellite products have recently become an alternative for water resources studies. A daily groundwater recharge estimation in the NW part of the Lake Chad Basin, using a soil–plant-atmosphere model (VisualBALAN), from ground- and satellite-based meteorological input dataset for non-irrigated and irrigated land and for the 2005–2014 period is presented. Average annual values were 284 mm and 30°C for precipitation and temperature in ground-based gauge stations. For the satellite-model-based Lake Chad Basin Flood and Drought Monitor System platform (CHADFDM), average annual precipitation and temperature were 417 mm and 29°C, respectively. Uncertainties derived from satellite data measurement could account for the rainfall difference. The estimated mean annual aquifer recharge was always higher from satellite- than ground-based data, with differences up to 46% for dryland and 23% in irrigated areas. Recharge response to rainfall events was very variable and results were very sensitive to: wilting point, field capacity and curve number for runoff estimation. Obtained results provide plausible recharge values beyond the uncertainty related to data input and modelling approach. This work prevents on the important deviations in recharge estimation from weighted-ensemble satellite-based data, informing in decision making to both stakeholders and policy makers.     

重力场可匹配区域选择研究

本文根据重力匹配辅助惯性导航需求,开展了重力场基准图的特征分析研究,提出了衡量可匹配性的特征指标体系,根据该指标体系建立了一个多通道的综合指标分布图,并引入了水平集理论,采用一种基于Mumford-Shah模型的全局化水平集的图像分割方法对重力场可匹配区域进行分割。通过重力匹配实验验证,结果表明,分割出的可匹配区域能达到提高匹配概率的作用。     

A prediction model for overlying rock thickness of subsea tunnel: A hybrid intelligent system

Abstract

The overlying rock thickness of a subsea tunnel controls its vertical line. It not only ensures the safety and stability of tunnel construction period and operation period, but also ensures the economy of subsea tunnel. In the current research, few papers give full consideration to the complex indicators of prediction the overlying rock thickness. However, in this study, a hybrid intelligent system was established to predict the overlying rock thickness of a subsea tunnel based on Qingdao Kiaochow Bay Subsea Tunnel, China. The sea depth, basic quality index of rock mass, soft soil layer thickness, permeability coefficient, and construction management level were selected as the main factors influencing the overlying rock thickness. Using the data obtained from project site exploration, objective weight factors were calculated using rough set theory, and subjective weight factors were calculated using the analytic hierarchy process. Furthermore, the combination of weights was obtained for each factor. Finally, the weight of influencing factors was incorporated into the extension model, and the overlying rock thickness of pending section was calculated. The results of overlying rock thickness prediction model are consistent with the actual value, indicating that the model has good engineering applicability and application value.