加速广义Laguerre多项式级数的Laplace变换的数值反演方法

本文利用Levin t-变换迭代法，对加速广义Laguerre多项式级数，提出了一种新的Laplace变换的数值反演方法，这种方法在精度上和数值稳定性上的效果都较好。     

拟M—阵和广义M—阵

在椭圆型偏微分方程数值解法中，经常遇到Ｍ－阵与Ｓｔｉｅｌｔ－ｊｅｓ－阵，本文进一步拓广Ｍ－阵的概念，并研究它们的性质及其在线性方程组迭代解法中的作用。     

基于MCMC模拟的MGPD模型及其在地质灾害风险度量中的应用

基于马尔科夫链蒙特卡洛(简记为MCMC)模拟的参数贝叶斯估计,对改进的广义帕累托分布(简记为MGPD)模型进行了优化,并利用该模型得到了地质灾害损失的在险损失值(简记为VaR)和条件损失值(简记为CVaR).以湖南娄底市地质灾害损失数据进行实证分析及模型适应性检验,结果表明:优化后的模型不仅具有很好的极值数据描述能力,而且具有较强的适用性.     

E－凸集的几个基本性质

利用比较与分析的方法，由E-凸集的定义出发，研究了E-凸集的若干基本性质．所得结果丰富并深化了凸分析的基本内容，拓宽了广义凸性在优化理论及其应用中的研究范围．     

The Feasible Control for the Day-operation of the Three-Gorge Cascade Hydropower Station

The feasible control problem is presented for the day-operation of the Three-Gorge Caseade Hydropower Station. The significance of the problem is explained. Basic propetties ofthe problem and the approaches to study it are discussed. Two methfods are given for solving theproblem. which are calculus of variation and linear programming. In the former. the Euler equationwith time-lag and the generalised two-point boundary conditions are obtained and the correspondingpractical implication is interpreted. In the latter. the rationality for the discrete model is exptainedand the computalional details are given for the implement software. some questions which should bepaid much attentfon and the corresponding propeels are prasented based on the numerical results andtheoretical analysis     

Predicting the age of fish using general and generalized linear models of biometric data: A case study of two estuarine finfish from New South Wales, Australia

Direct ageing of fish can be a laborious and expensive task when age estimates from a large population are required, and often involves a degree of subjectivity. This study examined the application of general and generalized linear models that predict the age of fish from a range of efficiently and objectively measured covariates. The data sampled were from yellowfin bream (Acanthopagrus australis (Sparidae) (Owen, 1853)) and sand whiting (Sillago ciliata (Sillaginidae) Cuvier, 1829) populations from New South Wales, Australia. The covariates evaluated in the models were fish length, otolith weight, sex and location (the estuary from which the fish were sampled). Akaike Information Criteria were used for model selection and residual plots of the final models revealed a satisfactory fit to the observations. The best fitting model for each species included all covariates. An additional investigation considered whether general and generalized linear models that predict age from two different categories of biometric information outperform age-length keys with respect to subsequent estimates of total mortality from catch-curve analysis. The two categories of biometric information differed in the ease and cost with which the information could be collected. The first category only included fish length and location as covariates, whilst the second category also included otolith weight and sex. It was found that traditional age-length keys outperformed the predictive models that estimated age from only fish length and location, because the results from the models were prone to significant bias. However, when otolith weight and sex were added as covariates to the predictive models, some of them, including a generalized linear model with a Poisson-distributed response variable, performed similarly to the age-length key. Given that otolith weight and the sex of fish are cheaper to quantify than age from a sectioned otolith in many situations, general or generalized linear models may represent a cheaper and faster method of estimating mortality compared to age-length keys. Such models can also easily incorporate the influence of spatial, temporal and demographic variation.     

Drivers of Setaria pumila (Poir.) Roem. et Schult growth and impact on forage quality in lowland Switzerland meadows

Invasive grasses (especially Setaria pumila (Poir.) Roem. et Schult) increasingly threaten meadows and pastures as a consequence of human impact and climate change. We conducted a study in 2012 and in 2013 to better understand the growing cycle and the influence of S. pumila on forage quality of lowland meadows. We observed a rapid increase of S. pumila presence and phytomass on the southern side of the Alps across the growing season. We measured (i) above‐ground phytomass, with a modified Corral‐Fenlon method; (ii) botanical composition using the linear point quadrat method; and (iii) grassland chemical composition by NIRs (near‐infrared spectroscopy) analyses. To test the hypothesis that S. pumila summer growth is related to specific climatic conditions, meteorological data (temperature, precipitation and evapotranspiration) were collected from meteorological stations near the study sites. Total phytomass was sorted into S. pumila and other species. We used a generalized linear mixed models (GLMM) and found the abundance of S. pumila to be inversely correlated with rainfall and the presence of other species, but positively correlated with temperature increase. The increase of S. pumila above‐ground phytomass production was linked to a reduction of forage quality.     

基于数据包络分析的灌区农业生产综合效率评价与分析

为评价中国灌区农业生产综合效率的空间差异性,采用数据包络分析(Data envelopment analysis,DEA)方法对全国440个灌区2010年的农业生产综合相对效率进行评估,并基于不同区域灌区农业生产投入及其冗余状况对生产效率提升途径进行探索。结果表明,8个灌区的相对效率为1.000,达到DEA有效;灌区间农业生产效率差异显著,绝大部分(327个)不足0.300,省区尺度生产效率无明显空间分布规律;各投入指标对应存在冗余灌区个数分别为319(有效灌溉面积)、369(绿水)、155(蓝水)、298(化肥)及207(农业机械);非DEA有效灌区5个投入指标的可减少量占所有评价单元投入总量的比例分别为23.8%、39.2%、18.1%、29.0%以及19.9%。综上可知,各非DEA有效灌区应根据自身投入指标冗余状况优化配置和管理资源以提高区域综合农业生产效率,其中绿水资源高效利用是全国范围内广泛面临的问题;东北和西北地区需注重水土资源配置效率提升,而南方粮食主产区应注重水肥高效利用机制的研究与实践。     

单栋塑料温室内多因子综合CFD稳态模拟分析

为分析单栋塑料温室内的综合环境:气流场、温度场、湿度场、CO2浓度场,建立了包括温室内外空间、室内作物和土壤层等的温室环境几何模型。将温室内的湿空气看作水蒸气、CO2和干空气的混合气体,在分析温室中太阳辐射、作物与环境的质热交换,动量及质能传递过程的基础上,对单栋塑料温室内的环境因子进行了稳态模拟。温室内热辐射传递过程采用蒙特卡罗法模拟方法;将室内作物简化为连续固体换热模型,采用剪应力输运模型(SST)表述温室内的空气紊流。结果显示:温室通风对温度、湿度和CO2分布的影响很大,温室内部上风向温度低,湿度小,同时CO2浓度也不高;温室下风向作物冠层的环境未达到优化状态;模型的预测值低于实测值,但变化规律相似,温度、湿度、CO2含量的预测相对误差分别低于8%、6%和7%。     

差分生长模型预测误差的分析

差分模型是一种特殊随机参数模型,仅有一个参数为随机参数。对于未参与抽样建模的林分,差分模型首先对应变量在林龄Aij0时的期望函数求解关于随机参数的表达式,然后用非随机参数的估计值和应变量在Aij0时的观测值Yij0分别取代对应参数和数学期望E(Yij0)来估计随机参数。显而易见,Yij0相当于E(Yij0)的估计值。由于这种特有的统计特征,经典非线性回归模型不能准确地估计差分模型预测误差的方差。针对这一不足,依据非线性回归模型预测误差的方差估计量的推导过程,导出了一个适用于差分模型的预测误差的方差估计量,并给出一个应用示例。所提出的估计量充分地考虑了重复观测数据的自相关性和Yij0对预测的影响作用。结果表明,该估计量能够描述未抽样林分预测误差的方差及其构成分量的变化趋势,而对于抽样建模的林分应该使用非线性回归模型的估计量进行预测误差分析。