Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner–Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.     

黑龙江省水稻单产增长潜力预测方法研究

水稻是黑龙江省的主要粮食作物。加入WTO后,水稻生产、贸易、进出口等方面都面临新的形势,同时水稻产量的稳定和增长对于国家粮食安全、人民生活水平提高以及农民奔小康都有着重要意义。因此,探讨了应用Peal曲线函数模型对黑龙江省水稻单产进行预测的方法。     

Prediction of the Economic Development for the Circumjacent Reservoir Region of the Longtan Hydropower Project Using Grey Quantitative Analog

In order to overcome some technical difficulties,we adopt ingenously the grey models combined with the quantitative analog method,and select the Dan Jiangkou Project which has accumulated practical operation data for a long time as the analog project to predict the economic influence for the circumjacent reservoir region of the Longtan hydropower project.On the basis of analog we have built various industrial economic grey models,and compare them with the corresponding predictions for the unconstructed reservoir case.The predictions of the former are greatly larger than the later ones.and hence provides a certain scientific basis for the central leaders to make a decision for constructing the huge hydropower project ultimateiy.     

A Kind of Directing Operation Expert Systems Based on Self-adaptive Predictor

In the general directing-operation expert systems.the information of directingoperation is often shown after the subprocess has finished,The aim of the thesis is to enhance thefunction of directing-operation,and suggest that we add the self-tuning predictor in the expertsystems and use it to direct the present operation.We have shown the case oftemperature-predicting experiment made in the small wine distillatorv so that we can illustrate thatit is feasible to use the predictor to direct the operation.     

煤与瓦斯突出综合预测指标临界值的优化

为了提高煤与瓦斯突出预测的准确性、保障采掘工作面的安全、高效推进和降低防突工程成本,根据“三率”(预测突出率、突出预测准确率、不突出预测准确率)各自具有的合理区间属性和权重,以张集煤矿采掘工作面为例,采用区间数关联决策方法,得出综合预测指标 F ′的最优化区间为［370,380］;根据加权灰靶决策方法,得出预测指标临界值排序为400、390、380等;取最优化区间和排序靠前的临界值的交集,得到煤与瓦斯突出综合预测指标 F ′的临界值为380,并开展现场应用。结果表明,考虑评价指标的区间属性,并取预测指标区间与排序靠前的临界值的交集作为煤与瓦斯突出预测综合指标 F ′的最优临界值方法是合理的。     

大型轴流泵装置性能预测的研究

以樊口泵站的工程实际为背景,运用CFD数值模拟技术和方法,以肘型进水流道,屈膝式出水流道及40CJ-95型轴流泵为具体对象,对泵装置整体进行全面系统的研究.在额定转速下,改变叶片安装角,分别模拟各种不同叶片安装角下的工况,预测水泵性能,并和实际特性曲线进行比较;分别改变转速和叶片安装角,针对模拟结果分析预测装置性能,与模型试验值进行对比.结果表明:用基于有限体积法的双方程紊流模型对泵装置整体进行数值仿真研究,是可行、有效的;并且通过与已有实验成果比较,得出模拟计算结果与试验值吻合较好,表明计算结果可信.     

城市工业用水量的灰色马尔可夫预测模型

灰色GM(1,1)是预测城市工业用水量的模型,这种模型不适合长期的、随机和波动性较大的数据序列预测,但是马尔可夫模型适合描述随机波动性较大的预测问题.可以将这两种模型结合,构建灰色马尔可夫预测模型.按特定的状态划分方法,先用灰色GM(1,1)预测模型进行预测,再用马尔可夫模型预测结果进行优化,使预测精度大大提高.最后以抚顺市为例,预测结果证明了该模型的优势.     

基于最小二乘支持向量机模型预测田面糙率

田面糙率是影响地面灌溉质量的重要参数。基于最小二乘支持向量机建立了两类4个田面糙率预测模型,并进行了验证。结果表明第一类模型预测值(即作物地采用LSSVM-N-I3、裸地采用LSSVM-N-I1,翻耕地采用LSSVM-N-I2)相对误差最大值为9.7%;第二类模型预测值(即LSSVM-N-II模型)相对误差最大值为10.5%,由此可见两类模型都具有较高的预测精度,可以用于田面糙率的预测。     

机械通风温室内部温度模型的试验验证

介绍了一种以温室机械通风和温室内作物冠层蒸发过程为主的温室温度数学模型,该模型具有结构简单、所有过程均为线性表达的特点,特别适合温室的在线适时控制。为了能够验证模型的可行性,进行了两种通风率条件下的试验。试验结果说明:在通风量足够高时,该模型能较好地预测温室内部温度。     

优化运行理论在泵站综合自动化系统中的应用

利用改进的神经元网络构建了泵站流量以及效率预测模型，并利用改进的遗传算法构建了泵站优化模型。将这两个模型应用到泵站综合自动化系统中，可以完成对泵站流量及效率的准确预测，并在此基础上实现泵站的优化运行。讨论了泵站优化运行理论在泵站综合自动化系统中应用的步骤和方法。