储备偏好影响下中国与欧盟天然气进口博弈

中国目前是世界第一大天然气进口国，但与欧盟相比，其天然气储备水平很低。为了应对各种不确定性以保障天然气的稳定供应，中国天然气储备水平未来将会有明显提升。天然气储备水平的变化将引起天然气进口需求的变化，进而通过中俄管道天然气的贯通影响欧盟天然气的进口策略。旨在从理论上分析中国天然气储备偏好变化对不同信息结构下天然气进口博弈的潜在影响。研究表明，当只有中国调整储备偏好时，中国在同时博弈中所获得的利润可以达到在主从博弈中主者的利润水平，此时欧盟的利益会受到损害；而当中国和欧盟均可以调整储备偏好时，中国和欧盟的均衡利润可能因为过度储备反而降低，俄罗斯则可能因此而获得更多的生产者剩余。本文还对天然气进口均衡价格、均衡进口量、利润水平等进行了定量分析，同时，利用天然气市场相关数据检验了本文结论的有效性和稳定性。     

Non-invasive genetic study and population monitoring of the brown bear (Ursus arctos) (Mammalia: Ursidae) in Kastoria region – Greece

The brown bear (Ursus arctos) in Greece is considered endangered but little is known about the genetic status and the exact size of local populations. Non-invasive genetic sampling was used in this study to investigate the genetic diversity and genetic structure of the brown bear population in the Kastoria region (northwest Macedonia, Greece) and to estimate its population size. Estimation of demographic parameters was based on innovative, well-evaluated methods that can provide estimates from a single sampling session. DNA was extracted from hairs, scat and blood samples and subsequent amplification of 10 microsatellite loci allowed the identification of a minimum number of 75 living bears in the study area while the mark–recapture-based analysis resulted in a point estimation of 219 individuals. Relatively high diversity values, lack of heterozygosity deficiency as well as estimated effective population size, support the Kastoria bear population having good conservation status.     

半空间上水平层状场地自振频率计算方法比较

为避免结构物与场地地基的共振效应,基于传统波速法、一致质量矩阵剪切质点系法及剪切梁法的基本原理,分析和比较了各方法计算场地自振频率的计算精度和影响因素.结果表明:传统波速法不能反映土层剖面结构特征的影响,而且仅在土层剖面在深度方向较为对称的情况下才能获得工程可接受的精度;一致质量矩阵剪切质点系法则表现出计算稳定、精度高的特点,且作为一种离散方法,具有良好的计算适应性和灵活性.     

基于微博文本的个性化兴趣关注点及情绪变迁趋势研究

随着社交网络的快速发展,人们可利用微博平台发表、分享自己的观点以及抒发某种情绪,进而产生了大量针对不同话题的博文和情绪信息,但传统的文本挖掘算法在处理这些短小且具富含个性化情感信息的微博文本方面有所欠缺。在此提出一种基于微博文本的特征权重计算方法,可据此得到博主在不同时间段的关注点,通过情绪分类,分析用户在不同时间段内的情绪变迁情况。实验结果证明此方法具有一定的可行性。     

基于Kriging模型的多点加点准则和并行代理优化算法

针对并行仿真环境下复杂工程系统的优化设计问题,提出一种基于Kriging模型、多目标策略和聚类方法的并行代理优化算法.该算法的多点加点准则,以同时优化期望改进准则和可行性概率准则为目标,首先生成兼具目标响应改进和可行域边界刻画功能的备选试验点集;再利用聚类方法从备选点集中选取多个有代表性的新试验点.通过两个数值算例和一个工程算例,将所提并行优化算法与已有算法做比较,结果表明所提算法具有更高的优化精度、效率和稳健性.     

鲸鱼优化相关向量机的网络控制系统变采样周期调度

针对资源受限的网络控制系统,提出一种基于鲸鱼优化相关向量机的变采样周期调度算法。通过网络监测模块获取网络带宽与数据传输时间数据,建立鲸鱼优化相关向量机的预测模型,实现对网络带宽及数据传输时间的预测。采用模糊推理计算系统各回路通信带宽的分配权重,进而结合通信带宽及数据传输时间的预测值对各闭环回路的采样周期进行计算,完成采样周期的实时调节。仿真结果表明,在资源受限条件下,所提算法保证了系统的稳定性与控制精度。     

Compressive sensing based multiuser detector for massive MBM MIMO uplink

Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.     

多精英采样与个体差分学习的分布估计算法

提出了基于多精英采样和差分搜索的分布估计算法EDA-M/D (Estimation distribution algorithm based on multiple elites sampling and individuals differential search)。EDA-M/D利用多精英个体独立采样生成子代来提升算法全局搜索能力,利用精英群体分布的σ²约束采样半径,实现种群从全局搜索逐步过度到局部搜索。当精英群体停滞时,劣势个体借助精英群体的μ和种群历史最优解进行差分搜索,帮助种群跳出局部最优解。通过多精英采样与差分搜索的自适应协同实现种群宏观信息与个体微观信息的有机融合。实验结果表明EDA-M/D在稳定性和搜索能力方面均表现出明显的优势。