基于自适应遗传算法的MRS-TEM联合反演方法研究

地面磁共振法(MRS)因具有定性、定量分析地下水能力,而备受关注.传统磁共振地层含水量反演多采用均匀半空间模型,忽略电阻率分布信息对结果的影响.针对这一问题,本文基于多层电介质中磁共振响应理论,提出MRS与瞬变电磁(TEM)联合反演方法,通过电阻率分布信息对含水量反演过程的实时修正,提高了解释结果的准确度.反演算法采用自适应遗传算法(AGA)进行,基于繁殖规则,动态调整交叉概率和变异概率,解决了标准遗传算法易未成熟收敛而难以得到全局最优解问题.模型数据表明,含噪10%情况下,联合反演仍能较准确地反映地下含水单元模型结构,对比MRS单独反演优势明显.同时,内蒙古白旗野外观测数据联合反演结果与钻井资料基本一致,充分验证了AGA反演算法的实用性及MRS-TEM联合反演的实际意义.     

利用超导重力数据探测Slichter模三重分裂信号

本文基于2004苏门答腊地震后全球地球动力学计划观测网中9台超导重力仪13200 h的连续重力观测数据,联合利用整体经验模态分解(EEMD)、最优序列估计(OSE)、积谱密度分析(PSA)和自回归估计(AR)方法,探测地球固态内核平动振荡模态(Slichter模)的三重分裂信号.利用EEMD提取常规预处理后的重力残差中包含目标频段的本征模态函数(IMFs)作为最终的重力残差之后,将每个台站的重力残差平均分成无重叠的3个子数据块,再应用OSE和PSA方法获取Slichter模三重分裂谱线的积谱密度,并采用AR方法估计各积谱中弱共振信号的中心频率及其误差.结果表明,结合OSE和PSA方法探测到三个清晰的谱峰,周期分别为5.8307±7.1×10-4 h、5.2161±8.1×10-4 h和4.7536±5.2×10-4 h,分别对应Slichter模三重分裂谱线m=-1、m=0和m=+1,且三个谱峰的周期与Crossley(1992)、Rochester和Peng(1993)、Peng(1997)和Rogister(2003)基于PREM地球模型给出的Slichter模理论周期非常接近,也与Ding和Shen(2013)建议的"可能的观测结果"较为接近.参考现有的理论和观测结果,本文认为这三个信号可能是Slichter模三重分裂谱线.     

SOTEM响应特性分析与最佳观测区域研究

电性源短偏移距瞬变电磁法(SOTEM)是目前研究和应用较为广泛的一种人工源时间域电磁法工作装置,对深部资源地球物理精细探测具有一定的实际意义.为了深入理解方法内涵并更好地进行推广应用,本文基于电性源瞬变电磁一维正演理论,研究了SOTEM地下感应电流扩散、多分量电磁响应平面分布、多偏移距衰减等特性,然后根据上述特性研究了SOTEM的最佳观测区域.研究结果表明:电性源在地下可以产生水平和垂直两个方向的感应电流.其中,水平感应电流又分为上部水平感应电流和下部水平感应电流(又称作返回电流),水平感应电流的极大值主要集中于发射源附近并垂直向下扩散;垂直感应电流极大值沿与地面呈45°角的方向向下、向外扩散,并且具有较低的振幅和较快的扩散速度.电性源激发的六个方向的电磁场分量都具有一定的探测能力,但是考虑到地面观测的方便性和各分量的传播、分布特点,大多数情况仅利用垂直磁场分量Hz(ðB/ðt)和水平电场分量Ex.其中,Hz仅对低阻目标体敏感,且敏感区域位于赤道向区域,并集中在发射源附近;Ex既对低阻体敏感也对高阻体敏感,对低阻体的敏感区域位于赤道向区域,而对高阻体的敏感区域位于轴向区域,并且敏感区域距发射源的距离与目标体埋深和围岩电性有关.     

基于GIS的无棣县耕地优化配置

通过对耕地质量的适宜性评价,利用多目标规划方法对不同耕地质量中的种植结构进行面积控制,借助Arc/Info和MapInfo等工具,实现耕地优化配置的自动化,使原来停留在理论探讨上的土地优化配置问题在方法论上有了补充.     

基于下一代四星转轮式编队系统精确和快速反演FSCF地球重力场

第一,由于重力卫星编队轨道的稳定性设计是建立下一代高精度和高空间分辨率地球重力场模型的关键,因此为保证下一代四星转轮式编队系统的稳定性,轨道根数的最优设计如下:(1)轨道半长轴a、轨道偏心率e、轨道倾角i和升交点赤经Ω保持不变;(2)每对卫星的近地点幅角ω和平近点角M分别相差180°;(3)初始近地点辐角ω设置于赤道处,初始平近点角M设计于极点处;(4)卫星编队系统椭圆轨道的半长轴和半短轴之比为2:1. 第二,基于下一代四星转轮式编队系统,利用星间速度插值法,通过相关系数(激光干涉测量系统的星间速度0.85、GPS接收机的轨道位置和轨道速度0.95、星载加速度计的非保守力0.90)、观测时间30天和采样间隔10 s,反演了120阶FSCF-1/2/3/4(Four-Satellite Cartwheel Formation)地球重力场,在120阶处累计大地水准面精度为1.162×10^-4 m,较目前GRACE地球重力场精度至少提高一个数量级. 第三,下一代四星转轮式编队系统具有低轨道高度、高精度测量、全张量观测、弱混频效应和强时变信号的优点.     

基于CGE模型的电力低碳转型速度调控策略研究——以粤港澳大湾区为例

为探讨粤港澳大湾区实现碳中和及电力低碳转型过程的供应安全,构建粤港澳大湾区动态CGE模型,设计51种情景模拟各类型发电量的年均变化幅度,以全社会福利最大化为评价指标,研究煤电退役到保底容量、煤电完全退役和气电达峰容量的最优时间节点和发展速度.结果表明:2020年煤电发电量以年均降低66亿kW?h幅度退役到2032年保底...     

非开挖钻进工程最优穿越曲线的计算

在非开挖钻进工程中,穿越曲线的设计是第一个关键的工作,而只有根据现场条件设计计算出合适的穿越曲线,才能保证整个钻进穿越工程的顺利进行和完成。本文在满足相关规范要求的基础上,建立了穿越曲线的计算模型,并利用MATLAB计算程序对其进行优化计算,确定最短穿越距离,使得穿越工程费用最经济。通过现场工程的验证,该计算模型对现场施工有一定的指导意义。     

水田井灌区的优化设计

水田井灌区主要是开发利用地下水资源发展农业灌溉,针对井灌区的运行特点,以干扰井群的水力计算理论为依据,通过建立目标函数及相应的约束条件,采用非线性规划的分析方法,提出水田井灌区规划优化设计井参(成井直径,成井深度,成井密度及涌水量)的求解公式和求解方法。     

Optimizing multi-resolution segmentation scale using empirical methods: Exploring the sensitivity of the supervised discrepancy measure Euclidean distance 2 (ED2)

Multiresolution segmentation (MRS) has proven to be one of the most successful image segmentation algorithms in the geographic object-based image analysis (GEOBIA) framework. This algorithm is relatively complex and user-dependent; scale, shape, and compactness are the main parameters available to users for controlling the algorithm. Plurality of segmentation results is common because each parameter may take a range of values within its parameter space or different combinations of values among parameters. Finding optimal parameter values through a trial-and-error process is commonly practiced at the expense of time and labor, thus, several alternative supervised and unsupervised methods for supervised automatic parameter setting have been proposed and tested. In the case of supervised empirical assessments, discrepancy measures are employed for computing measures of dissimilarity between a reference polygon and an image object candidate. Evidently the reliability of the optimal-parameter prediction heavily relies on the sensitivity of the segmentation quality metric. The idea behind pursuing optimal parameter setting is that, for instance, a given scale setting provides image object candidates different from the other scale setting; thus, by design the supervised quality metric should capture this difference. In this exploratory study, we selected the Euclidean distance 2 (ED2) metric, a recently proposed supervised metric, whose main design goal is to optimize the geometrical discrepancy (potential segmentation error (PSE)) and arithmetic discrepancy between image objects and reference polygons (number-of segmentation ratio (NSR)) in two dimensional Euclidean space, as a candidate to investigate the validity and efficacy of empirical discrepancy measures for finding the optimal scale parameter setting of the MRS algorithm. We chose test image scenes from four different space-borne sensors with varying spatial resolutions and scene contents and systematically segmented them using the MRS algorithm at a series of parameter settings. The discriminative capacity of the ED2 metric across different scales groups was tested using non-parametric statistical methods. Our results showed that the ED2 metric significantly discriminates the quality of image object candidates at smaller scale values but it loses the sensitivity at larger scale values. This questions the meaningfulness of the ED2 metric in the MRS algorithm’s parameter optimization. Our contention is that the ED2 metric provides some notion of the optimal scale parameter at the expense of time. In this respect, especially in operational-level image processing, it is worth to re-think the trade-off between execution time of the processor-intensive MRS algorithm at series of parameter settings targeting a less-sensitive quality metric and an expert-lead trial-and-error approach.     

THE DOWNSCALING FORECASTING OF SEASONAL PRECIPITATION IN GUANGDONG BASED ON CLIMATE FORECAST SYSTEMS PRODUCTS

The Climate Forecast Systems （CFS） datasets provided by National Centers for Environmental Prediction （NCEP）, which cover the time from 1981 to 2008, can be used to forecast atmospheric circulation nine months ahead. Compared with the NCEP datasets, CFS datasets successfully simulate many major features of the Asian monsoon circulation systems and exhibit reasonably high skill in simulating and predicting ENSO events. Based on the CFS forecasting results, a downscaling method of Optimal Subset Regression （OSR） and mean generational function model of multiple variables are used to forecast seasonal precipitation in Guangdong. After statistical analysis tests, sea level pressure, wind and geopotential height field are made predictors. Although the results are unstable in some individual seasons, both the OSR and multivariate mean generational function model can provide good forecasting as operational tests score more than sixty points. CFS datasets are available and updated in real time, as compared with the NCEP dataset. The downscaling forecast method based on the CFS datasets can predict three seasons of seasonal precipitation in Guangdong, enriching traditional statistical methods. However, its forecasting stability needs to be improved.