利用IGS星历预报GPS卫星轨道

在动力学轨道拟合以及轨道积分的基础上,提出了基于IGS精密星历的GPS卫星轨道预报方法。该方法首先利用已知的IGS精密星历作为虚拟观测值,采用动力学方法拟合出GPS卫星的初始轨道和动力学参数,然后再通过积分来预报GPS卫星的轨道。主要讨论了基于不同弧段的IGS星历时,该方法对GPS卫星轨道的拟合和预报情况。研究结果显示:对于6 d弧段以内的IGS精密星历,其拟合轨道与IGS精密星历差值的三维RMS值均优于4 cm,随着拟合弧段的增加,拟合残差变大;当利用2～6 d弧段的IGS星历来预报GPS轨道时,大部分卫星第1天、第7天和第30天的三维预报精度可优于0.1 m、3 m和100 m。其中,2d弧段的IGS星历对GPS卫星第1天和第7天的预报结果最好,5 d弧段的IGS星历对GPS卫星第30天的预报结果最好。     

洋浦近岸海域污染控制规划方案优化——Ⅰ.排污口位置优选

在洋浦近岸海域计算潮流场基础上,计算预选排污口附近海水质点运动轨迹及预测污染物浓度分布,最后,从环保角度出发,推荐了洋浦地区各开发区的排污口位置,为洋浦近岸海域污染控制规划方案的制定及其优化提供了依据。     

基于双隐层ANN模型的叶绿素a浓度智能预报方法

利用2019年5月WZ02生态浮标监测数据,建立了两种不同隐层人工神经网络(ANN)模型的叶绿素a(Chl-a)智能预报方法,并对单隐层和双隐层模型的预测结果做了对比.结果表明:双隐层结构预测结果精度更高,泛化能力更强,一定程度上说明了深层学习比浅层学习对信息的主要特征提取能力更有优势.同时,对数据样本集合进行了系统预...     

射阳港潮汐与乘潮进港

根据实测和航行实践分析比较发现,射阳港潮汐同潮汐预报表有一定偏 ,实际高潮 比预报值高,实际低潮位比预报值低,遍地比预报要早,低潮时比预报要迟。本文研究了这一变化规律,对确定科学的乘潮进港时间及港口规划、运营有指导意义。     

基于PSR-WSVM模型的边坡位移预测

为建立高精度的边坡位移预测模型，采用相空间重构（PSR）将边坡位移时间序列数据转换为多维数据，同时构造小波核函数改进的支持向量机模型，建立PSR-WSVM模型并应用于边坡位移预测。将PSR-WSVM模型预测结果与传统支持向量机（SVM）模型、小波支持向量机（WSVM）模型和基于相空间重构的支持向量机（PSR-SVM）模型预测结果进行对比，通过平均绝对误差（MAE）、平均绝对误差百分比（MAPE）和均方根误差（RMSE）3个精度评价指标验证PSR-WSVM模型的可行性。工程实例结果表明，PSR-WSVM模型预测结果的3个精度评价指标都优于另外3种模型，边坡位移预测的精度明显提升。     

1999年以来台湾及邻近海域7.5级以上强震前的条带现象

中国台湾地区地处欧亚板块与菲律宾海板块之间,地震活动频繁．本文报道了 我国台湾地区及其邻近海域1985～2002年间5．5级以上地震的条带内外频度比分 布,并着重研究了1999—2002年中发生的3次7．5级以上地震前的条带现象．其结 果表明:台湾地区近期发生的3次7．5级以上大地震前,5．5级以上地震呈条带分 布．这些条带符合条带内地震个数Nin≥6的条件,符合条带内、外频度比Nin／(Nin Nout)≥75％的条件,也符合条带长宽比大于5的要求,只是与板内地震条带相比,条 带的长度较短．     

基于机器学习模型的区域土壤重金属空间预测精度比较研究

为识别区域土壤重金属的空间变异特征并厘清其影响因素,本研究构建了多元线性回归（MLR）、弹性网络回归（ENR）、随机森林（RF）、随机梯度提升（SGB）、堆叠（stacking）集成模型、反向传播神经网络（BP-ANN）、基于模型平均的神经网络集成（avNNet）、线性核支持向量机（SVM-L）和高斯核支持向量机（SVM-R）共九种机器学习模型,利用山东省中部土壤重金属（Cd、Cu、Hg、Pb和Zn）和环境辅助变量数据,开展区域土壤重金属空间预测精度比较研究。结果表明：RF对五种重金属空间预测的决定系数（R²）介于0.263~0.448之间,平均绝对误差（MAE）和均方根误差（RMSE）分别小于8.408和10.636,预测值/实际值（P/O）均接近于1,对五种重金属的预测效果均较为理想,是研究区土壤重金属空间预测的最优模型;SVM-R整体预测性能仅次于RF,各项精度评价指标均相对稳健,可作为备选模型;其余七种模型的预测性能均明显低于RF和SVM-R。RF的空间预测结果显示,研究区五种重金属呈现出相似的空间分布格局,含量均由研究区东北部向西南部递减,包括东北部、北部和南部3个高值区,且高值区与当地工业–交通密集区的分布格局一致,反映出人类活动是研究区土壤重金属空间分异的主要影响因素。本研究可为区域土壤污染调查、评价和管控提供科学参考。     

Predicting the visualization intensity for interactive spatio-temporal visual analytics: a data-driven view-dependent approach

The continually increasing size of geospatial data sets poses a computational challenge when conducting interactive visual analytics using conventional desktop-based visualization tools. In recent decades, improvements in parallel visualization using state-of-the-art computing techniques have significantly enhanced our capacity to analyse massive geospatial data sets. However, only a few strategies have been developed to maximize the utilization of parallel computing resources to support interactive visualization. In particular, an efficient visualization intensity prediction component is lacking from most existing parallel visualization frameworks. In this study, we propose a data-driven view-dependent visualization intensity prediction method, which can dynamically predict the visualization intensity based on the distribution patterns of spatio-temporal data. The predicted results are used to schedule the allocation of visualization tasks. We integrated this strategy with a parallel visualization system deployed in a compute unified device architecture (CUDA)-enabled graphical processing units (GPUs) cloud. To evaluate the flexibility of this strategy, we performed experiments using dust storm data sets produced from a regional climate model. The results of the experiments showed that the proposed method yields stable and accurate prediction results with acceptable computational overheads under different types of interactive visualization operations. The results also showed that our strategy improves the overall visualization efficiency by incorporating intensity-based scheduling.     

The simulation of LUCC based on Logistic-CA-Markov model in Qilian Mountain area,China

The Qilian mountain area was examined for using the Logistic-CA-Markov coupling model combined with GIS spatial analyst technology to research the transformation of LUCC, driving force system and simulate future tendency of variation. Results show that:(1) Woodland area decreased by 12.55%, while grassland, cultivated land, and settlement areas increased by 0.22%, 7.92%, and 0.03%, respectively, from 1986 to 2014. During the period of 1986 to 2000, forest degradation in the middle section of the mountain area decreased by 1,501.69 km~2. Vegetation cover area improved, with a net increase of grassland area of 38.12 km~2 from 2000 to 2014.(2) For constructing the system driving force, the best simulation scale was 210m×210m. Based on logistic regression analysis, the contribution(weight) of composite driving forces to land use and cover change was obtained, and the weight value was more objectively compared with AHP and MCE method.(3) In the natural scenarios, it is predicted that land use and cover distribution maps of Qilian mountain area in 2028 and 2042, and the Lee-Sallee index test was adopted. Over the next 27 years(2015–2042), farmland, woodland, grassland, settlement areas show an increasing trend, especially settlements with an obvious change of 0.56%. The area of bare land will decrease by 0.89%. Without environmental degradation, tremendous structural change of LUCC will not occur, and typical characteristic of the vertical zone of the mountain would remain. Farmland and settlement areas will increase, but only in the vicinity of Qilian and Sunan counties.     

礁膜配子放散条件的研究

本文报道了礁膜配子的放散与温度、光照、比重的关系。结果表明，自然海区的礁膜在白天大量放散配子。配子放散的适宜温度为１９－２１℃；光照为２０００－５０００ｌｘ时能促进配子大量放散出来；配子放散的适宜比重为１．０５－１．０２５；这些研究结果将为礁膜人工育苗提供一些科学依据。