柔性坐标测量机参数辨识方法

设计了一种六自由度关节式柔性坐标测量机,并对该测量机测量方程中的参数进行了辨识,提出了一种快速简易的单点锥窝标定方法。该方法基于单点锥窝提供的空间单点基准,利用非线性最小二乘中的高斯-牛顿法,求解测量机测量方程的参数值。实验结果表明,该方法能够有效提高测量机的整体精度,且操作简单、计算效率高。     

固定效应对槟榔江水牛体重影响的研究

[目的]槟榔江水牛为我国目前为止发现的唯一本土河流型水牛,具有产奶性能高、肉用性能好的特点,为了进一步阐明槟榔江水牛的生长发育规律,本文收集云南腾冲县巴福乐槟榔江水牛2004~2011年生长发育数据资料,研究性别、月份和年度等固定效应对体重的影响。[方法]应用SAS分析性别、月份、年度等非遗传因素对槟榔江水牛体重的影响,并且用MTDFREML软件分析了固定效应值。[结果]本研究结果表明,槟榔江水牛性别对初生重具有显著影响,公犊平均初生重(35.04kg)显著高于母犊(32.63kg);月份对母牛初生重没有显著影响,公牛的效应值比母牛的较大。[结论]月份对槟榔江水牛的体重有显著的影响,可能与饲料的季节性供给有关。     

基于广义混合效应模型的云冷杉林天然更新计数方法研究

天然更新是森林恢复较好的办法,对未来林分结构和生物多样性具有深远的影响。更新模型能够模拟天然更新的现实和未来状况,为森林经营者提供准确的森林计划。以吉林省汪清林业局2013年设置的12块云冷杉针阔混交林为例,选择泊松和负二项分布形式,考虑样地间的随机效应,构建基于林分因子的云冷杉针阔混交林天然更新模型。结果表明：各个树种对林分因子的反应不一,白桦更新株数与林分每公顷株数和平均直径均呈负相关;红松和水曲柳更新株数不受各个林分因子的影响,更新株数是随机的;冷杉更新株数与林分每公顷断面积呈负相关;色木槭和云杉更新株数均与林分平均直径呈负相关。在考虑样地的随机截距效应后,模型的模拟效果显著提高。在构建天然更新模型时,林分密度是十分重要的因子,如果要人工促进天然更新,就要科学合理的采取经营措施,以确保合理的林分密度。另外样地间的差异是不容忽略的因素,需要利用混合效应模型方法来降低预测误差。     

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 Algorithm of Searching out the Least and Most Loops by Making Use of Direction Factor

Based upon the conception of the least loop,the most loop and direction factor presented by the author firstly,the algorithm of searching out the least and most loops has been designed.By building the adjoining matrix, confirming the start-point of searching,vectorizing the searching sides,calculating the direction factor of adjoining sides,we can search out the next side of the least loop or the most loop rapidly.With a valid searching side being confirmed at every searching and the searching scope being reduced by forming degenerate graph,the time compexity of the algorithm is much less. In the research of the automatic calculating system of construction quantities, the problem of houses partition and out-wall partition had been solved succesfully by utilizing this searching algorithm.     

变步长的最小二乘递推算法

针对固定步长的最小二乘递推算法在信号辨识中采集数据量大、辨识速度较慢的缺点,提出了变步长的最小二乘递推算法,在保证同等辨识精度的条件下, 采集的数据明显减少,大大提高了辨识速度。     

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.     

基于自然光照反射光谱的温室黄瓜叶片含氮量预测

利用便携式光谱辐射仪测量了自然光照条件下温室黄瓜叶片的光谱反射率,并计算了反射率光谱的一次微分光谱。反射率光谱以及一次微分光谱与叶片含氮量的相关分析表明,温室内光谱特性与叶片含氮量相关性最大的敏感波段分别是505～664 nm和685～722 nm。当利用原始光谱进行分析时,通过变量筛选得到了4个敏感波长,分别是568、596、640和664 nm。偏最小二乘回归分析(PLSR)以及归一化颜色指数(NDCI)分析都表明,建模时的相关系数R_C>0.800,模型验证时的相关系数R_V>0.700。对微分光谱进行的相关分析结果表明,利用单一敏感波长520 nm就可获得理想模型,建模时的相关系数为0.880,模型验证时的相关系数为0.787。对比原始光谱的PLSR模型与一阶微分光谱的一元线性回归模型可以得知,原始光谱以及一阶微分光谱都可用于温室内叶片含氮量的预测,而且一阶微分光谱在一些特殊的波长处具有更高的预测能力,这些模型将成为开发便携式作物长势诊断仪器的技术基础。     

Estimation of genetic variance components and heritabilities for cut-flower yield in gerbera using least squares and maximum likelihood methods

Summary Genetic variance components and heritability were estimated for cut-flower yield of gerbera in the Davis population using ordinary least squares and maximum likelihood methods. The overall estimate of narrow-sense heritability is 0.33 based on least squares (LS) and 0.31 based on maximum likelihood (ML). The results of the study indicate that (1) ML and LS provide very similar results if sample size is large enough, suggesting both are useful for plant breeding programs; (2) about one third of the variation in gerbera cut-flower yield is additive, implying selection in cut-flower will be successful; and (3) although additive variation gradually decreased, heritability remained near 0.27 suggesting there is still potential variation in the population for further selection.     

标准击实试验的一种数据处理方法

针对土工实验中标准击实试验数据处理存在的问题，提出了利用最小二乘法进行高次多项式插值的一般准则：若残差χ^2值最小及χ^2分布的累积概率较小，则通过其选取的多项式阶数是适宜的,用MATLAB实现之，简单易行，从而为求解岩土的最大干密度和最佳含水量提供了理论依据，它可望在土工试验数据处理中得到推广和应用。