Direct assimilation of satellite radiance data in GRAPES variational assimilation system

Variational method is capable of dealing with observations that have a complicated nonlinear relation with model variables representative of the atmospheric state, and so make it possible to directly assimilate such measured variables as satellite radiance, which have a nonlinear relation with the model variables. Assimilation of any type of observations requires a corresponding observation operator, which establishes a specific mapping from the space of the model state to the space of observation. This paper presents in detail how the direct assimilation of real satellite radiance data is implemented in the GRAPES-3DVar analysis system. It focuses on all the components of the observation operator for direct assimilation of real satellite radiance data, including a spatial interpolation operator that transforms variables from model grid points to observation locations, a physical transformation from model variables to observed elements with different choices of model variables, and a data quality control. Assimilation experiments, using satellite radiances such as NOAA17 AMSU-A and AMSU-B （Advanced Microwave Sounding Unit）, are carried out with two different schemes. The results from these experiments can be physically understood and clearly reflect a rational effect of direct assimilation of satellite radiance data in GRAPES-3DVar analysis system.     

Warming experiments underpredict plant phenological responses to climate change

Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.     

A comparative analysis of the evolution of imperfect mimicry

Although exceptional examples of adaptation are frequently celebrated, some outcomes of natural selection seem far from perfect. For example, many hoverflies (Diptera: Syrphidae) are harmless (Batesian) mimics of stinging Hymenoptera. However, although some hoverfly species are considered excellent mimics, other species bear only a superficial resemblance to their models and it is unclear why this is so. To evaluate hypotheses that have been put forward to explain interspecific variation in the mimetic fidelity of Palearctic Syrphidae we use a comparative approach. We show that the most plausible explanation is that predators impose less selection for mimetic fidelity on smaller hoverfly species because they are less profitable prey items. In particular, our findings, in combination with previous results, allow us to reject several key hypotheses for imperfect mimicry: first, human ratings of mimetic fidelity are positively correlated with both morphometric measures and avian rankings, indicating that variation in mimetic fidelity is not simply an illusion based on human perception; second, no species of syrphid maps out in multidimensional space as being intermediate in appearance between several different hymenopteran model species, as the multimodel hypothesis requires; and third, we find no evidence for a negative relationship between mimetic fidelity and abundance, which calls into question the kin-selection hypothesis. By contrast, a strong positive relationship between mimetic fidelity and body size supports the relaxed-selection hypothesis, suggesting that reduced predation pressure on less profitable prey species limits the selection for mimetic perfection.     

基于均衡7×2交叉验证的模型选择方法

交叉验证策略广泛应用于分类问题的模型比较和模型选择中．文章提出一种均衡7×2交叉验证并给出了相应的构造方法．文章以分类回归树（CART）为考察模型,对比了采用均衡7×2交叉验证、组块3×2交叉验证、标准5折和10折交叉验证在模型选择中的性能．模拟结果表明,在小规模数据集上,均衡7×2交叉验证方法选择到真模型的概率明显高于其余三种交叉验证的选择方法．     

一种新的支持向量回归机的模型选择方法

针对支持向量回归机的模型选择问题,将模型选择问题转化为一个非线性系统的状态估计问题,然后引入无迹卡尔曼滤波进行求解,提出一种新的基于无迹卡尔曼滤波的模型选择方法(UKF-SVR).对标准数据集和太阳黑子数平滑月均值进行仿真实验,结果表明,UKF-SVR与粒子群算法相比,该方法全局寻优能力更强,保证了支持向量回归机泛化能...     

带工业约束和交易费用的离散投资组合最优化

该文研究带有工业约束和凹的交易费函数的离散单因素投资组合模型.与传统的投资组合模型不同的是,该模型中投资组合的决策变量是交易手数(整数),其最优化模型是一个非线性整数规划问题.为此提出了一个基于拉格朗日松弛和连续松弛的混合分枝定界算法,而且分别采用股票市场的真实数据和随机产生的数据来测试该算法的有效性.     

一种基于数据挖掘的入侵检测系统模型

提出了一种基于数据挖掘技术的入侵检测系统模型,该模型是一个核模型,具有很好的扩展能力和适应能力,该模型因使用了元检测引擎来综合处理来自各个基本检测引擎的数据而提高了检测结果的准确性。文中还构建了一个基于数据挖掘的入侵检测原型系统来分析几种典型的数据挖掘技术的实际应用效果,讨论了数据预处理和特征提取问题。     

基于评价指标体系的科技报告竞争力评价系统

为了解决科技报告评价问题, 提出了竞争力评价指标体系的指标选取和指标权重, 给出科技报告竞争力评价指标体系的评价公式; 根据设计的的竞争力评价公式模型, 结合科技报告竞争力评价系统设计, 采用计算机手段实现了吉林省科技报告竞争力评价系统。 评价实例证明, 该评价系统真正地实现了自动化的单篇科技报告评价或多篇科技报告对比评价, 为科研项目管理提供一定的参考依据。     

Pattern of nucleotide substitution at major histocompatibility complex class I loci reveals overdominant selection

The major histocompatibility complex (MHC) loci are known to be highly polymorphic in humans, mice and certain other mammals, with heterozygosity as high as 80-90% (ref. 1). Four different hypotheses have been proposed to explain this high degree of polymorphism: (1) a high mutation rate, (2) gene conversion or interlocus genetic exchange, (3) over dominant selection and (4) frequency-dependent selection. In an attempt to establish which of these hypotheses is correct, we examined the pattern of nucleotide substitution between polymorphic alleles in the region of the antigen recognition site (ARS) and other regions of human and mouse class I MHC genes. The results indicate that in ARS the rate of nonsynonymous (amino acid altering) substitution is significantly higher than that of synonymous substitution in both humans and mice, whereas in other regions the reverse is true. This observation, together with a theoretical study and other considerations, supports the hypothesis of overdominant selection (heterozygote advantage).     

New generation of multi-scale NWP system （GRAPES）： general scientific design

A new generation of numerical prediction system GRAPES （a short form of Global/Regional Assimilation and PrEdiction System） was set up in China Meteorological Administration （CMA）. This paper fo- cuses on the scientific design and preliminary results of the numerical prediction model in GRAPES, including basic idea and strategy of the general scientific design, multi-scale dynamic core, physical package configuration, architecture and parallelization of the codes. A series of numerical experiments using the real data with horizontal resolutions from 10 to 280 km and idealized experiments with very high resolution up to 100 m are conducted, giving encouraging results supporting the multi-scale application of GRAPES. The results of operational implementation of GRAPES model in some NWP centers are also presented with stress at evaluations of the capability to predict the main features of precipitation in China. Finally the issues to be dealt with for further development are discussed.     

基于ITAFSVM的微阵列数据特征选择和分类

支持向量机已经被成功应用于基因表达谱数据分析。但是,仍有开放问题需要解决:①支持向量机不能自动进行基因表达谱数据的特征选择;②支持向量机的参数优选没有简单有效的办法。一种新型具有良好特性的支持向量机——全间隔自适应模糊支持向量机(TAFSVM)被提出。并且提出一种新的遗传算法——智能遗传算法(IGA)来设计一个TAFSVM分类器,称为ITAFSVM,同时优化TAFSVM参数集和特征选择,并且结合10-fold交叉验证来确定其泛化能力。最后将ITAFSVM应用于四种基因表达谱数据集。通过与进化支持向量机(ESVM)方法、粗糙集与径向基神经网络组合(RBF-RBFNN)方法进行了比较,实验结果表明运用ITAFSVM不仅可以自动进行基因表达谱数据特征选择,而且分类精度和稳定性都较高,速度更快。     

解读量子力学的基本假定

量子力学,即便对物理专业的大学生而言,也是深奥难懂的．我们认为：要真正掌握量子力学,最佳的路径是弄清楚量子力学的5个基本假定．基于这个认识,首先我们提出一个麻将骰子模型,该模型能够同时解释量子力学的5个基本假定．然后运用这个麻将骰子模型,结合具体例子逐个解读量子力学的5个基本假定．因此,这个麻将骰子模型及其解读有助于普通读者对量子力学的理解。     

Reconstructing the Nonlinear Dynamical Systems by Evolutionary Computation Techniques

We introduce a new dynamical evolutionary algorithm（DEA） based on the theory of statistical mechanics and investigate the reconstruction problem for the nonlinear dynamical systems using observation data. The convergence of the algorithm is discussed. We make the numerical experiments and test our model using the two famous chaotic systems （mainly the Lorenz and Chen systems）. The results show the relatively accurate reconstruction of these chaotic systems based on observational data can be obtained. Therefore we may conclude that there are broad prospects using our method to model the nonlinear dynamical systems.     

多特征筛选与支持向量机相融合的图像分类模型

针对图像分类中的特征选择问题,提出一种多特征筛选与支持向量机相融合的图像分类模型.首先提取图像的多种特征,并对特征进行归一化处理;然后根据平均影响值对特征进行筛选,选择一组最优的特征子集;最后采用支持向量机构建图像的多分类器.采用图像数据集SIMPLIcity进行仿真实验验证该模型的有效性.实验结果表明,该模型降低了图像分类的开销,提高了图像分类性能.     

超饱和设计的变量选择

超饱和设计被广泛应用于工业统计试验和其它科学试验的初期阶段。本文采用逐步回归分析法对文献「１１,１２」的超饱和设计进行了统计模拟,验证了该设计在变量选择上的有效性,也显示了逐步回归分析法是一种很好的应用于超饱和设计的数据分析方法。     

面向车身结构分析的骨架驱动模型变形方法

提出一种面向车身结构分析的骨架驱动模型变形方法,实现有限元模型的有效重用.根据给定车身结构有限元模型的几何特点,定义描述车身结构的骨架曲线与包围车身结构的控制体.建立骨架曲线与模型控制体的约束关系,用户可对骨架曲线进行编辑,得到目标控制体形状.最终应用体变形方法,重构内嵌的有限元模型.数值实例表明,骨架驱动的模型变形方法能够实现有限元模型的有效重用,并为用户提供了直观便捷的交互方式.     

MIMO系统发射端多天线选择保障物理层安全传输

针对MIMO系统信号传输策略中单天线选择方案在增大系统保密容量方面存在的局限性,本文提出发射端多天线选择方案以保障物理层安全通信。文中首先在已知全局信道状态信息的理想条件下讨论最优多天线选择方案;然后考虑较为实际的情况,即在未知窃听方信道状态信息条件下提出次优多天线选择方案;最后,为改进次优方案在低信噪比条件下系统保密容量较小的不足,提出次优多天线选择发射功率分配方案。通过理论推导保密容量表达式和数值分析,结果表明,与现有单天线选择方案相比,所提的多天线选择方案有效地提高了系统的保密容量。     

中文文本分类研究

使用k近邻、支持向量机和最大熵模型进行中文文本分类的研究,对目前应用较多的k近邻、支持向量机和最大熵模型,分别进行了基于特征词布尔值和基于特征词词频的中文文本分类实验。实验结果显示,在相同的条件下最大熵方法的分类性能最好,支持向量机次之,k近邻稍差。同时发现,在分类过程中引入了词语频率信息时,分类器的性能略有变化,对于最大熵分类准确率下降1%~2%,对于k近邻有所上升,对于支持向量机则相当。除去文本的特殊性影响,这表明不同程度的词语的信息对不同的机器学习算法有不同的影响。     

Do search and selection operators play important roles in Multi-objective Evolutionary Algorithms: A case study

Multi-objective Evolutionary Algorithm (MOEA) is becoming a hot research area and quite a few aspects of MOEAs have been studied and discussed. However there are still few literatures discussing the roles of search and selection operators in MOEAs. This paper studied their roles by solving a case of discrete Multi-objective Optimization Problem (MOP): Multi-objective TSP with a new MOEA. In the new MOEA, We adopt an efficient search operator, which has the properties of both crossover and mutation, to generate the new individuals and chose two selection operators: Family Competition and Population Competition with probabilities to realize selection. The simulation experiments showed that this new MOEA could get good uniform solutions representing the Pareto Front and outperformed SPEA in almost every simulation run on this problem. Furthermore, we analyzed its convergence property using finite Markov chain and proved that it could converge to Pareto Front with probability 1. We also find that the convergence property of MOEAs has much relationship with search and selection operators. Foundation item: Supported by the National Natural Science Foundation of China (60133010,70071042,60073043) Biography: Yan Zhen-yu( 1977-), male, Master student, research interests: computational intelligence, evolutionary computation.