混合访问控制模型在测绘应用系统中的应用

本文在分析测绘系统开发与应用中测绘数据的复杂性,以及大部分测绘系统都包含业务流程等特点的基础上,除了RBAC模型的角色授权外,加入了任务对操作进行授权,对RBAC模型进行了有效的扩展,使其更具通用性.该方法有效解决了传统的RBAC模型在测绘系统应用中存在的弊端,对其他应用系统建设同样具有理论指导.     

离心场中风力电机桩基复杂加载测试设备的研制

桩基础是近海风力发电中经常采用的基础形式,承受着包括低频风循环荷载在内的复杂荷载组合。为了采用离心模型试验来研究风机桩基础特性,研制了离心场中风机桩基础复杂加载测试设备。该套设备除了可以施加水平向和竖向静力荷载外,还实现了离心场中长时间低频率的水平循环加载,并能够实现多种荷载同时或者先后施加。通过一系列测试试验,验证了该套设备的有效性,满足离心模型试验中对模拟风机桩基础的复杂荷载要求。初步试验结果表明,桩顶水平位移随着水平荷载循环周数的增加而增大,但增长速率逐渐减小,至一定周数后,桩顶位移趋于稳定,土体变形主要集中在桩周一定区域内     

Predicting Diel,Diurnal and Nocturnal Dynamics of Dissolved Oxygen and Chlorophyll‐a Using Regression Models and Neural Networks

Human‐induced and natural interruptions with continuous streams of observational data necessitate the development of gap‐filling and prediction strategies towards better understanding, monitoring and management of aquatic systems. This study quantified the efficacy of multiple non‐linear regression (MNLR) versus artificial neural network (ANN) models as well as the temporal partitioning of diurnal versus nocturnal data for the predictions of chlorophyll‐a (chl‐a) and dissolved oxygen (DO) dynamics. The temporal partitioning increased the predictive performances of the best MNLR models of diurnal DO by 45% and nocturnal DO by 4%, relative to the best diel MNLR model of diel DO ($r_{{\rm adj}}^{2} = 68.8\%$ ). The ANN‐based predictions had a higher predictive power than the MNLR‐based predictions for both chl‐a and DO except for diurnal DO dynamics. The best ANNs based on independent validations were multilayer perceptron (MLP) for diel chl‐a, generalized feedforward (GFF) for diurnal and nocturnal chl‐a, MLP for diel DO, GFF for diurnal DO, and MLP for nocturnal DO.     

基于层次任务网络规划的分布式协同地理建模任务分解方法研究

为了有效地实现分布式协同地理建模中的合作规划和资源共享,通过分析分布式协同地理建模中任务分解过程,探讨地理建模任务的功能结构、计算复杂性、组织多方性和时空尺度等分解依据,采用层次任务网络(HTN)规划形式化表达地理建模任务,设计了基于顺序任务分解(OTD)的地理建模任务的递归分解算法,模拟领域专家寻求合作规划地理建模任务的思考方式。以分布式流域水文模型SWAT作为试验案例,开发并实现了地理建模任务HTN规划器,为分布式协同地理建模环境中的任务分解方法提供了新的思路。     

尼日尔三角洲深水勘探研究面临的挑战及其对策

面对深水勘探开发钻井和工程难度大、经济投资成本高的特点,针对深水区复杂油气藏,本文首先在深水研究区从深水重力构造形成机制和深水沉积储层研究入手,创新了深水研究区成藏规律认识。在深水重力构造研究方面,发现其由陆向海的演化模式,按演化和特征分成3种类型,建立深水沉积和重力控制下的构造模式;在深水沉积研究方面,以刻画深水沉积特征为基础,分析了海平面升降影响和重力流密度对深水沉积的控制作用,建立了两种深水沉积模式;然后通过研究重力构造、深水沉积与油气成藏三者的关系,确立了重力构造对深水油气成藏的主控作用,以及深水沉积储层与油气富集规律的关系,建立了深水油气成藏模式。在此基础上,提出了以断层为线索,落实构造,追踪油气,以沉积为单元,计算储量和资源量,进行深水高效勘探评价的新方法。并将上述思路应用到深水复杂油气藏勘探研究中,取得了较好的实际效果。     

Accuracy and reliability-based region-specific recalibration of dynamic pile formulas

Many state departments of transportation and consulting firms continue to use dynamic formulas because they are simple and inexpensive as compared to the preferred dynamic loading test with signal matching. Efforts to reduce the error and uncertainty associated with dynamic formulas are therefore warranted until dynamic monitoring becomes standard for every driven pile. However, dynamic formulas calibrated to national test pile databases have indicated inaccuracy and high uncertainty in the capacity prediction using dynamic formulas. A region-specific dynamic load test database was used to assess the accuracy and uncertainty in the Janbu, Danish and FHWA Gates formulas, recalibrate the equations for local conditions (construction practice, geology) and to generate resistance factors for use with Load and Resistance Factor Design (LRFD). Following recalibration, the capacity predictions became more accurate, and an observed dependence of the accuracy on the magnitude of resistance was eliminated for most driving conditions (e.g. end-of-driving, restrike). Previously reported static load test data were used to incorporate the transformation error associated with using the dynamic capacity to predict an equivalent static capacity. Resistance factors for use in Load and Resistance Factor Design (LRFD) were developed in consideration of American Association of State Highway and Transportation Officials–recommended load statistics and target reliability indices. Efficiency factors were used to assess the economic performance of each dynamic formula. Comparison of the accuracy and uncertainty of the recalibrated equations to a nationwide calibration illustrated the advantage of using a geologic-specific database for the calibration of resistance factors.     

基于事件的土地划拨时空数据库若干思考

业务化运行的图文办公系统给土地划拨时空数据库的设计提出了新的要求,即不但要记录时空地块状态的变化,还必须描述表达引起变化的原因（审批事件）与变化过程。本文针对这一问题分析了土地提事件及其与时空地块状态因果关系的方法,并借鉴主动数据库领域的研究成果对土地划拨事件及其发生过程进行形式化表达。该方法还为此类系统流程控制的实现提供了新的思路,并为其数据库ＣＡＳＥ工具的设计与实现提供了基础。     

基于卫星地面站天线状态预测的任务再规划

集成运行控制系统(Integrated Operation and Control System,IOCS)是极轨气象卫星地面应用系统的重要系统之一,其主要作用之一是规划多卫星地面站接收任务,确保全球资料的完整获取。当卫星地面站某个天线出现异常或不可用时,若仍按原有的任务规划进行数据接收,将直接造成全球资料的不完整,因此需要研究卫星地面站天线状态的预测和相应的任务再规划技术,从而及时发现和处理卫星地面站的天线异常、降低连续多轨数据接收失败风险,最终达到提高极轨气象卫星数据接收成功率的目的。文章设计了基于统计分析的卫星地面站天线状态预测方法,并研究了对后续系统运行改变最小、易实现和结果可复核的任务再规划方法。     

Using data‐driven methods to explore the predictability of surface soil moisture with FLUXNET site data

Soil moisture (SM) is a key variable of land surface‐atmosphere interactions. Data‐driven methods have been used to predict SM, but the predictability of SM has not been well evaluated. This study investigated what variables and methods can be used to better predict SM for leading times of 7 days or longer with a global coverage of FLUXNET site data for the first time. Three machine‐learning models, that is, Bayesian linear regression, random forest, and gradient boosting regression tree, are used for the prediction. Variables including atmospheric forcing, surface soil temperature, time variables (year, day of year, and hour), the Fourier transformation of time variables, and lagged SM (7‐ to 14‐day lagged) were sequentially added into models. A framework with five experiments is designed for factorial exploration of SM predictability. A stepwise method was used to build the best models for each site. The performance of regression models became better when adding more explaining variables in most cases. The results showed that from 50 to 95% of variation of the best models can be explained. The important explaining variables are lagged surface SM, followed by day of year, year, soil temperature, and atmospheric forcing. The predictability of SM depends highly on SM memory characteristics and the persistence of seasonality. The effect of SM memory characteristics on SM prediction as an initial condition question has been widely discussed in this paper. Our results also provide an insight that mechanisms of seasonality effects on SM should be also paid more attention to.