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。     

大规模富社团网络的时空混沌同步

以Plankton时空混沌系统作为网络节点,通过非线性耦合构成富社团(rich-club,RC)网络,研究其时空混沌同步规律.首先给出了RC网络中连接节点之间的非线性耦合函数的一般性选取原则.进而基于Lyapunov稳定性定理,理论分析了实现网络同步的条件.最后,通过仿真模拟检验了网络的时空混沌同步效果.仿真研究表明,RC网络中各富节点之间以及这些富节点各自星形连接的子网络中的所有节点均实现了完全同步.     

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.     

利用相关逼近法建立定位与姿态数据的同步模型

根据海道测量精密测量的需求,对姿态与定位数据融合的同步方法进行了研究。通过GPS大地高数据和升沉数据,建立了一种基于相关逼近原理的定位与姿态数据同步模型。该模型能够确定定位与姿态数据的相对延时,实现两类数据在同一时间基准下的同步。实例计算表明,定位与姿态数据的相对延迟时间已成为两类数据融合应用中必须考虑的因素。由同步模型解算后,GPS大地高数据与总升沉数据体现了更好的一致性,由此也验证了模型的有效性。     

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.     

加强目标观测,服务防灾减灾

以深入浅出的方式介绍了目标观测的定义、历史、确定目标观测敏感区的方法,以及实施目标观测与防灾减灾的关系;并以欧洲中期天气预报中心目标观测业务化为例,简明地概括了目标观测的实施过程;结合国内目标观测研究现状,对中国目标观测的未来提出了看法。     

基于自适应峰值分解的广义局部频率时频分析方法

往复压缩机振动信号具有复杂的多源冲击特性,表现较强的非平稳性,传统的时频分析方法难以提取有效的故障特征.以傅氏变换为基础的传统频率概念和以希尔伯特变换为基础的瞬时频率概念存在固有缺陷,提出一种广义局部频率的概念,并结合自适应峰值分解方法,实现信号时频分布的构造途径;与HHT时频分析方法进行仿真对比,并应用到往复压缩机振动信号故障特征提取.结果表明,基于自适应峰值分解的广义局部频率方法有效揭示往复压缩机不同故障的多源冲击振动信号时频特征,为往复压缩机故障诊断提供一种新的手段.     

一种自适应匹配子空间亚像元目标探测方法

为了克服基于线性混合模型的高光谱遥感影像亚像元目标探测方法的缺陷, 提出了一种基于全限制性线性分解的自适应匹配子空间探测方法。首先利用交叉相关光谱匹配技术求得各个像元所含端元类别信息, 然后根据端元类别信息和全限制性分解的结果构造自适应匹配子空间探测算子, 利用端元类别信息在探测中动态选择端元, 降低端元数目估计偏差对探测结果的影响, 提高探测器对目标与背景的可分性。实验证明, 该方法与其他基于线性混合模型的亚像元目标探测方法相比, 可以更好地克服端元数目估计偏差对探测结果的影响, 无论是端元个数低估还是     

基于波束控制的卫星导航接收机抗干扰算法研究

卫星导航接收机抗干扰技术是接收机设计的一项关键技术。在研究基于功率反演的空域自适应抗干扰算法基础上,提出了采用基于波束控制的抗干扰算法,并进行了仿真计算,结果表明：该算法明显提高了接收机抗干扰性能。     

Explicit integration of a porosity‐dependent hydro‐mechanical model for unsaturated soils

An adaptive substepping explicit integration scheme is developed for a porosity‐dependent hydro‐mechanical model for unsaturated soils. The model is referred to as the modified σ –Θ model in this paper, which features the employment of the subloading surface plasticity and the stress–saturation approach. On numerical aspects, convex/nonconvex subloading surfaces in the σ –Θ space may result in incorrect loading–unloading decisions during the integration. A new loading–unloading decision method is developed here to solve the problem and then embedded into the explicit integration scheme for the modified σ –Θ model. In addition, to enhance the accuracy of the explicit integration, local errors from both hydraulic and mechanical components are included in the error control for each substep. A drift correction method is also developed to ensure the state point lies on the subloading surface in the σ –Θ space within a set error level. The performance of the loading–unloading decision method for the modified σ –Θ model is discussed through comparing it with the conventional loading–unloading decision method. The importance of involving the hydraulic component in the error control is also demonstrated. The accuracy and efficiency of the proposed adaptive substepping explicit integration scheme for the modified p–Θ model are also studied via several numerical examples. Copyright © 2016 John Wiley & Sons, Ltd.