基于机器视觉的导航定位技术

对导航定位中的曲线导航问题进行研究,采用单目视觉导航定位的方法采集多幅导航线图像,首先进行了远距离标定,建立实际行走的距离与偏航角度以及目标物偏离中心位置的距离与像素大小的数据库,再用得到的数据库,根据几何的方法计算出导航精度,在本实验中,基本依靠单目视觉技术完成了曲线导航的任务。     

飞机播种造林中的GPSMAS导航技术及其定位精度

GPSMAS结合了GPS和G IS技术,通过编写程序实现对GPS卫星定位数据的接收、传输和处理,把当前定位数据适时转化为可视图像,具有准确高效的图示导航功能。GPSMAS导航定位的精度取决于GPS接收机定位精度和播区设计测点精度。其所达精度完全能满足飞机播种造林(种草)导航的需求。     

基于遥感影像的昆明中心城区绿地信息提取

以昆明中心城区遥感影像为研究数据,采用基于面向对象分类的研究方法,按照监督分类的思想,将地物分为城市绿地、林地、裸地、水体、建筑和道路6种类型,运用支持向量机的分类器对绿地信息进行提取,并根据总体分类精度和kappa系数的大小对分类结果进行验证,结果表明:城市绿地信息提取精度良好,符合城市绿地调查的精度标准,认为此种绿地信息提取方法值得推广运用。     

基于机器学习的高光谱湿地植被分类研究

为实现湿地植被的精细分类和高精度制图,为湿地管理部门提供准确的决策依据,以美国加州萨克拉门托—圣华金水域的典型湿地植被为研究对象,以高光谱影像为数据源,结合野外GPS采样点,对典型湿地植被的光谱反射率作一阶导数和二阶导数处理,基于均值置信区间原理筛选特征波段,基于单因素分析法筛选能够明显区分植被类型的植被指数。联合特征波段和植被指数构建特征集,利用机器学习C5.0决策树生成知识规则并提取湿地植被信息。结果表明,基于机器学习C5.0决策树的湿地植被提取总体精度为80.09%,Kappa系数为0.792,与最大似然法比较,总体精度提升10.79%,Kappa系数提升0.105,说明基于机器学习的C5.0决策树法能够实现植被的精细分类,方法切实可行。     

Mixed-effect non-linear modelling for diameter estimation along the stem of Tectona grandis in mid-western Brazil

This study evaluated the efficiency of taper functions and the application of mixed-effect modelling for diameter estimation along the stems of Tectona grandis. We sampled 266 trees of Tectona grandis, measuring the diameter at relative heights for volume determination, grouping the data according to three form-factor classes. Six taper functions were fitted, selecting the function with better fit performance. Six taper functions were fitted, selecting the function with better fit performance. The selected function was fitted in its basic formulation, and with the mixed non-linear modelling technique in different scenarios, and for the stem stratified in three portions of the total height. The precision and selection of the adjusted models were evaluated regarding the coefficient of determination, standard error of estimate, the Akaike information criterion, bias, quadratic error and absolute bias. According to the statistical criteria used, the model of Kozak was selected for the adjustments. For diameter estimation, the scenario with two coefficients as random effects provided an accuracy increase of 11.91%, and the mixed non-linear modelling better estimated the stem diameter for the stratified stems. In conclusion, the model of Kozak can be used to describe the stem shape of Tectona grandis, and the mixed-effect non-linear model approach was the best technique to estimate diameter along the stem of Tectona grandis.     

基于遥感的塞罕坝机械林场树种分类研究

随着遥感应用的不断推广,各应用领域对遥感图象的监督分类结果的精度要求越来越高。在监督分类中有两个非常关键的问题:一是训练样本选取;二是分类器选择。本论文应用监督分类中的不同分类器对塞罕坝机械林场进行树种分类,对其结果进行分析比较,选择合适的分类器提高分类精度。     

基于TM数据的遥感分类方法对比研究

以香格里拉县2009年Landsat5～TM遥感影像为实验数据,利用最大似然法（MLC）以及最小距离法两种方法进行了遥感分类方法研究,主要从分类精度方面对两种方法进行了对比分析,结果表明：最大似然法分类结果明显优于最小距离法,但作为传统的分类方法,二种方法分类精度都不够高。     

高效液相色谱法和光度法测定苯酚的对比

分别对液相色谱法和4-氨基安替比林分光光度法,测定苯酚的精密度、检测限及准确度等,进行对比和分析.结果表明:色谱法和光度法精密度和准确度均较高,但光度法操作简便且检出限较低,费用少,建议作为酚醛胶木制品苯酚释放的定量方法.     

Accuracy of imputation of single nucleotide polymorphism marker genotypes from low‐density panels in Japanese Black cattle

Using target and reference fattened steer populations, the performance of genotype imputation using lower‐density marker panels in Japanese Black cattle was evaluated. Population imputation was performed using BEAGLE software. Genotype information for approximately 40 000 single nucleotide polymorphism (SNP) markers by Illumina BovineSNP50 BeadChip was available, and imputation accuracy was assessed based on the average concordance rates of the genotypes, varying equally spaced SNP densities, and the number of individuals in the reference population. Two additional statistics were also calculated as indicators of imputation performance. The concordance rates tended to be lower for SNPs with greater minor allele frequencies, or those located near the ends of the chromosomes. Longer autosomes yielded greater imputation accuracies than shorter ones. When SNPs were selected based on linkage disequilibrium information, relative imputation accuracy was slightly improved. When 3000 and 10 000 equally spaced SNPs were used, the imputation accuracies were greater than 90% and approximately 97%, respectively. These results indicate that combining genotyping using a lower‐density SNP chip with genotype imputation based on a population of individuals genotyped using a higher‐density SNP chip is a cost‐effective and valid approach for genomic prediction.