多源地理空间矢量数据关联分析

针对多源地理空间矢量数据多来源、难以集成综合利用这一现状,本文提出了多源地理空间矢量数据关联方法,并以此为基础构建了多源地理空间矢量数据关联的可视与计算查询系统。首先,对多源地理空间矢量数据关联的概念及分类进行了定义。然后,以此为基础,提出了关联关系构建技术：自适应四叉树编码技术、扫描线技术、几何匹配及语义匹配技术。最后,为实现关联关系的直观展示,设计了原型系统。关联技术的提出可建立起多源地理空间矢量数据之间的关联关系,原型系统的构建也为用户综合利用多源地理空间矢量数据提供了平台,提高了数据的利用率及数据查询的效能。     

多模式自适应水下无线通信网络框架研究

对当前典型的水下无线通信网进行分析,针对水声、光、射频3种通信模式在水下无线通信中的优缺点,提出基于软件无线电技术的多模式自适应水下无线通信网络的概念及其框架结构,并对其中的自适应调制解调方式展开研究.结合MAC层协议,提出一种跨层的自适应调制解调解决方案,即通过收发双方的握手信息携带当前信道状态,由发射方根据握手信息,判断双方通信距离,预计信道未来状态,结合需要传输的数据量,自适应选择合适的通信模式和调制方式,并利用握手信号通知接收方,从而实现在通信网络范围内数据或指令的快速可靠传输.     

黑潮流域海温适应性观测敏感区诊断方法研究

敏感区诊断是适应性观测的关键问题,集合变换卡尔曼方法(EnsembleTransformKalmanFilter,ETKF)是目前主要的诊断方法之一。将集合变换卡尔曼方法应用于海洋环境适应性观测,根据ROMS海洋模式数据构建海表温度集合预报,以黑潮流域宫古海峡附近海域为验证区进行敏感区诊断计算,分析不同间隔时间条件下敏感区分布情况,结合模拟系统观测试验验证在敏感区进行适应性观测对预报质量的提升效果。结果表明,在诊断所得敏感区内添加观测能够提升预报质量;随时间间隔增大,敏感区向上游区域平移且预报质量提升效果减小;与在验证区整体添加观测相比,敏感区观测对预报质量提升效果基本相同并且观测成本明显减少。     

捷联式航空重力扰动矢量解算及误差补偿

介绍捷联式航空重力矢量测量的基本原理,利用波数相关滤波（WCF）、比力线性校正的方法对重力扰动的水平和垂向分量进行误差补偿,评定内符合精度。对国产捷联式航空重力矢量仪的某次试验数据进行处理,以验证和评估航空重力矢量仪的性能。结果表明,在半波长分辨率为7.5 km时,6条重复测线的重力扰动水平分量经波数相关滤波处理后,东、北向分量的平均内符合精度分别从9.77 mGal、9.18 mGal提高到5.95 mGal、3.83 mGal;对比力的垂向分量线性校正后,将解算的重力扰动垂向分量再用WCF方法处理,其平均内符合精度从1.27 mGal提高到0.59 mGal。     

改进的最小生成树自适应空间点聚类算法

针对传统的最小生成树聚类算法存在使用全局不变阈值确定噪声边,聚类需要用户根据经验确定初始化聚类参数,如“边权值倍数容差”,“边长变化因子”等,聚类不能发现局部噪声的问题,本文提出了一种改进的最小生成树自适应空间点聚类算法。该算法在无需用户输入参数的前提下,克服主观因素的影响,根据最小生成树边长的数理统计特征定义裁剪因子。算法首先从宏观层面对最小生成树进行首轮删枝操作,消除全局环境下的噪声边,进而根据各子树的边长统计情况,自适应设定局部裁剪因子,进行第二轮删枝操作,消除局部环境下的噪声边。最后,采用1个模拟数据和1个实际应用验证算法的有效性,结果表明本文提出的改进算法在无需人为提供经验参数的环境下能够发现任意形状、不同密度的簇,能够准确的识别出空间点中的噪声数据,从而能够实现空间点数据背后隐藏信息的自动挖掘。     

一种基于OpenMP的高效GPS卫星钟差实时估计方法

提出基于单观测值的Kalman滤波快速计算方法,并引入共享存储并行编程（OpenMP）技术实现协方差快速更新,从而实现非差GPS卫星钟差的快速实时计算。均匀选取55个IGS参考站,计算2017-03-20~03-30采样率为60 s的卫星钟差。与IGS事后30 s钟差相比,两者具有很好的一致性,RMS互差优于0.5 ns。选取未参与钟差解算的10个IGS参考站进行精密单点定位,结果表明,实时静态PPP水平方向精度优于2 cm,高程方向精度为2~4 cm;实时动态PPP水平方向精度为2～4 cm,高程方向精度为4～6 cm,能够满足实时PPP的精度要求。该方法在主频1.2 GHz服务器上8线程并行模式下单历元耗时4 s,相比串行模式效率提升1/3。     

一种基于熵权法的小波去噪复合评价指标

传统的评价指标在真值未知的情况下不能满足小波去噪质量评价的要求。为此,借助变化率特征重新构建均方根误差变化量和平滑度变化量两个指标,利用熵权法定权将归一化后的两个指标线性组合,所得到的新指标即为复合评价指标。该方法借助指标的变化率随分解层数的增加表现出明显的收敛特性来确定去噪最优分解层数。实验表明,该方法能够在真值未知的情况下准确地指导小波分解,确定去噪最优分解层数,从而达到最优去噪效果。     

Understanding marine ecosystem based management: A literature review

Ecosystem based management takes into account the interconnectedness and interdependent nature of ecosystem components and emphasizes the importance of ecosystem structures and functions which provide a range of services. The concept has now been adopted by many international agreements and national governments and is in the process of being implemented. This paper seeks to review the literature and to analyze the understanding of the subject. The term is defined and its implementation in fisheries and for all marine uses is analyzed. It has been concluded that to understand marine ecosystem based management one must consider ecosystems as complex adaptive systems which can show changes at higher levels from actions and processes occurring at lower levels. Recognizing that humans are part of these complex adaptive systems is vital in that their actions along with other processes can lead to transformations in ecosystem functioning. This recognition is also important to show how society can sustainably exploit these resources and that the inclusion of all stakeholders in the management process is necessary to legitimize the process. The uses of the precautionary principle along with adaptive management are seen to be useful tools in implementing these insights into the management of natural resources. Finally, the need for reducing consumption of fish is considered.     

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.     

集合卡尔曼滤波在流域水文模型流量预报中的应用

针对流域降雨入渗过程,引入集合卡尔曼滤波(EnKF)理论,视整个边坡流域为一个随机动态系统,将边坡流域流量观测值作为系统的输出,用集合卡尔曼滤波模型来描述系统的状态;结合流域流量计算方法,实现水文模型参数的随机动态估计,在有效获得待估参数的同时还给出估计值的不确定性.通过数值算例表明,集合卡尔曼滤波可以有效地对含噪声的量测数据进行处理,能够跟踪水文模型的动态变化.相对于常用最优化算法,集合卡尔曼滤波同时给出反演结果和先验知识的后验分布,显示出更好的实时性和可靠性.