老盐井组井型互换再利用工程实践

水平钻井连通水溶采卤一直是开采井矿盐资源最常用和最经济有效的手段,但由于地层条件复杂、饱和卤水结晶、套管破损等因素造成盐井组采卤运行过程中通道堵塞,一直是制约盐井组运行年限的主要原因。近些年,对堵塞井组修治常用方法有憋压、通井、开窗侧钻,其中水平井开窗侧钻重新对接现有溶腔在很多盐田区块修井中被广泛应用。在河北宁晋石盐田Y2-Y4井组修井过程中,存在老溶腔无法再利用的情况,此时老溶腔成为井组二次对接的“累赘”。在该区块首次采用井组井型互换（水平井改直井,直井改水平井）的方法,避开了老溶腔,实现了老井组的再利用。     

基于模糊预测对象的证据权方法及其在土地沙漠化评价中的应用

为了使在地理信息系统中被广泛用于点事件预测的证据权方法能对面事件进行评价和预测, 提出了一种新的基于模糊训练层的证据权方法.它是一种更广泛的证据权方法, 与普通证据权方法所不同的是, 它的训练层是模糊集合, 其取值是它的隶属度.通过适当的变换也可以把点训练层转换为模糊集合.因此, 该方法可以对面事件、点事件和线事件进行评价和预测.该方法可以处理训练层和证据层均为模糊集合的情况, 被称为双重模糊证据权方法.作为该方法的一个应用实例, 本文介绍毛乌素沙漠边缘的晋陕蒙地区土地沙漠化评价的应用实例.      

浙江省人口健康脆弱性评估及影响因素分析

运用集对分析法从敏感性和应对性2个方面对浙江省11个地市的人口健康脆弱性进行评估。研究表明：① 从敏感性和应对性2个维度对城市人口健康脆弱性进行评估的方法具有一定可靠性,但在突发大型流行性病毒感染疫情的情境下仍需进一步完善;② 各地市脆弱性指数排名与敏感性指数保持较高一致性,而与应对性指数则表现出异质性和随机性,认为降低敏感性是降低城市人口健康脆弱性指数的关键;③ 城市人口健康脆弱性评价还应该增加城市对大型突发公共卫生事件的敏感性和应对能力的考量,相应的评估方法和模型仍有待进一步研究。     

运用人工鱼群算法的3D扫描碎片重建探究

针对传统三维碎片拼接匹配过程中依赖单一特征及存在误差累积的问题,提出了一种运用鱼群算法的全局最优匹配方法。该方法先对碎片点云数据进行多特征提取,结合纹理、专家经验信息对混合在一起的多种类型碎片进行粗糙集分类,之后采用鱼群算法的最优解求得最佳匹配方案。实例验证所提全局匹配方法具有能力强、与初始位置无关及较强的稳健性等特点,为三维碎片的全局匹配提供了一种有效的解决方案。     

基于椭球不确定性的平差模型与算法

测量平差模型中的参数通常存在一些不确定的附加信息或先验信息,充分利用它们可以对部分参数进行约束,从而保证参数解的唯一性和稳定性。本文利用椭球集合描述不确定性,建立了一个新的带有椭球不确定性的平差模型。以两个椭球交集的外接椭球的特征矩阵的迹最小平差准则,分析了不确定度的传播规律,给出了带有椭球不确定性的平差方法。最后,通过算例验证了算法的有效性,说明了平差解与带权混合估计的关系。     

基于加权约束的单体建筑物点云表面重建算法

建筑物点云表面重建在高精度城市测绘、虚拟现实等领域有十分广泛的应用前景。由于建筑物的几何形态多变,重建算法普遍存在计算速率慢、拟合精度低和模型结构不完整的问题。为此,本文以单体建筑物为研究对象,提出基于加权约束的单体建筑物点云表面重建算法,在表面初始化过程中充分考虑数据对结构拟合的贡献。在此基础上,构建基于正则集的单体建筑物表面重建算法,实现建筑物拟合过程中的加权拟合误差、近邻结构平滑的同步优化。针对多类建筑物三维点云的实验结果表明,相比传统的建筑物重建策略,本文的加权约束方法可根据不同类型的点云数据设计自适应权重,并选择模型拟合中最优的权重函数,在高噪声、低精度点云数据下能得到更高精度的单体建筑物表面模型。     

Mapping the farming-pastoral ecotones in China

Conventional farming-pastoral ecotones methods of delineating were not quantitative and could not fully show their spatial distribution. The present paper attempts to develop quantitative methods for mapping farming-pastoral ecotones in China. Nine indicators, related to temperature, precipitation and altitude aspects, were selected to quantify ecological susceptibility of vegetation （crops and forage）. Methods of analytic hierarchy process （AHP） and expert score ranking combined with fuzzy set theory were applied to assign the weight for each indicator and to define the membership functions. The geographic information system （GIS） was used to manage the spatial database and conduct the spatial analysis. According to the spatial calculation of evaluation model integrated with GIS, the ecological susceptibility of vegetation （crops and forage） was mapped. Three different zones, pastoral area, farming-pastoral ecotones and farming area, were classified by spatial cluster analysis and the maximum likelihood classification for the numeric map of vegetation ecological susceptibility by GIS. This map was validated by the economic statistical result based on the ratio of the output value from animal husbandry in total output value of agriculture by the National Bureau of Statistics in China, indicating that the mapping of the farming-pastoral ecotones may be accepted.     

基于云理论、粗集和模糊神经网络的区域橡胶种植适宜度评估模型

针对橡胶种植适宜性评估,基于云理论、粗集理论和模糊神经网络理论,提出了一种适宜度评估模型。该模型将转化的样本数据进行粗集简约,通过模糊神经网络得出评价因子的隶属函数,计算评价等级。研究结果表明,此模型能够科学、快速、准确地分析出橡胶种植最适宜区、适宜区、次适宜区和不适宜区。     

Estimation of parameters in a split functional model of geodetic observations (<Emphasis Type="Italic">M</Emphasis><Subscript>split</Subscript> estimation)

The paper presents a method of estimating parameters in two competitive functional models. The models considered here are concerned with the same observation set and are based on the assumption that an observation may result from a realization of either of two different random variables. These variables differ from one another at least in the main characteristic (for example, outliers can be realizations of one variable). A quantity that describes the opportunity of identifying a single observation with one random variable is assumed to be known. That quantity, called the elementary split potential, is strictly referred to the amount of information that an observation can provide about two competitive assumptions concerning the observation distribution. Parameter assessments that maximize the global elementary split potential (concerning all observations), are called M _split estimators. A generalization of M _split estimation presented in the paper refers to the theoretical foundation of M-estimation. An erratum to this article can be found at     

Adaptive Predictive Inverse Control of Offshore Jacket Platform Based on Rough Neural Network

The offshore jacket platform is a complex and time-varying nonlinear system,which can be excited of harmful vibration by external loads.It is difficult to obtain an ideal control performance for passive control methods or traditional active control methods based on accurate mathematic model.In this paper,an adaptive inverse control method is proposed on the basis of novel rough neural networks (RNN) to control the harmful vibration of the offshore jacket platform,and the offshore jacket platform model is established by dynamic stiffness matrix (DSM) method.Benefited from the nonlinear processing ability of the neural networks and data interpretation ability of the rough set theory,RNN is utilized to identify the predictive inverse model of the offshore jacket platform system.Then the identified model is used as the adaptive predictive inverse controller to control the harmful vibration caused by wave and wind loads,and to deal with the delay problem caused by signal transmission in the control process.The numerical results show that the constructed novel RNN has advantages such as clear structure,fast training speed and strong error-tolerance ability,and the proposed method based on RNN can effectively control the harmfid vibration of the offshore jacket platform.