“花间隐榭，水际安亭”——基于华南植物园水榭和桂林芦笛岩水榭的营境分析

华南植物园水榭和桂林芦笛岩水榭是20世纪七八十年代岭南园林建筑的两处经典作品。它们与明代造园专著《园冶》里"花间隐榭,水际安亭"的字句遥相呼应,以现代主义建筑的创作风格构造出中国传统山水居游的惬意情境。以这两个经典现代风景建筑为例,尝试从情境、场景和身体体验3个不同角度,具体探讨风景建筑的营境操作。情境旨在针对建筑总体布局进行分析;场景则着眼于空间组合的探讨;最后从身体体验出发,讨论建筑的细部设计。     

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。     

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。     

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。     

基于NNARMAX模型的地下水位预报研究

区域地下水系统是一个受多种因素影响的复杂的非线性动态系统 ,应用遗忘因子的递归最小二乘( RLS)算法进行训练 ,采用通过减少网络节点间的连接权值 ,进而裁减冗余节点来选择适宜的网络拓扑结构 ,建立了非线性自回归滑动平均神经网络 ( NNARMAX)模型 ,地下水位预报结果表明 :通过对网络结构的优化达到了自动确定非线性自回归模型阶数和影响因素的选择 ,能有效地表示区域地下水动态系统内部及其外部诸多影响因素间的不确定关系 ,是预测区域地下水动态变化较为有效的方法之一。     

CO 2与土壤水分交互作用的番茄光合速率预测模型

为了实现不同土壤水分管理下的CO 2气肥精细控制,建立了番茄作物不同生长阶段的光合速率预测模型。实验设置了4个CO 2浓度与3个土壤水分条件的交互处理,利用无线传感器网络长期实时监测温室内环境信息,采用LI-6400XT型光合速率仪定时采集作物净光合速率信息;并用BP神经网络分别建立了番茄苗期、花期和果期的光合速率预测模型。预测模型的验证结果表明,对于苗期预测模型,预测值与实测值之间的决定系数 R 2为0.925;花期预测模型的决定系数 R 2为0.920,果期预测模型的决定系数 R 2为0.958;番茄各生长期的光合速率预测模型均具有较高的预测精度。在不同土壤水分条件下改变CO 2浓度,得到的CO 2浓度与光合速率预测曲线与实测值相近,可反映实际土壤水分管理下的CO 2浓度最优值,对指导不同土壤水分条件下CO 2气肥的精细调控具有重要意义。