控制工程造价不是盲目压价

本文对工程造价管理角度进行了论述,从不同的角度分析了控制工程造价的方法,阐明如 何科学地控制工程造价。     

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.     

西北旱区喷灌条件下紫花苜蓿生长特征与品质指标的关系

西北旱区由于独特的气候条件,生产的苜蓿干草品质好,产量高。如何根据苜蓿的田间指标估测干草品质参数,对于苜蓿草产品生产销售具有重要意义。研究在喷灌条件下不同灌溉量对紫花苜蓿的生长品质的影响,并利用生长指标对紫花苜蓿的品质进行预测。试验于2014至2015年于中国农业大学石羊河流域生态节水试验站进行为期2年的田间试验。试验共设3个灌溉处理:A₁灌溉量为100%紫花苜蓿蒸腾蒸散量(ETc),A₂,A₃的灌溉量分别为A₁处理的66%,33%,以及一个不灌溉处理A₄。结果表明,苜蓿生长指标如株高(H)和茎叶比(SLR)随生育期的推进呈上升趋势,而鲜干比(FDR)呈下降趋势;所有生长指标随着灌溉量的减少均呈下降趋势。在品质方面,随着生育期的推进,所有处理的粗蛋白(CP)呈下降趋势,而中性洗涤纤维(NDF)和酸性洗涤纤维(ADF)则呈现上升趋势;随着灌溉量的降低,NDF与ADF呈下降趋势,而CP则呈上升趋势。各生长指标与品质指标的拟合结果表明,H和SLR均与各品质指标显著线性相关(P<0.001),且H与品质拟合结果相关系数最高(R²>0.900),而FDR则与各品质指标不显著。这些结果表明,在田间管理较好,长势良好,杂草与病虫害发生较少的情况下,可以用株高对苜蓿干草品质做出预测。     

Genetic analysis for sow stayability at different parities in purebred Landrace and Large White pigs

Genetic parameters for sow stayability were estimated from farrowing records of 10,295 Landrace sows and 8192 Large White sows. The record for sow stayability from parity k to parity k + 1 (k = 1, …, 6) was 0 when a sow had a farrowing record at parity k but not at parity k + 1, and 1 when a sow had both records. Heritability was estimated by using single-trait linear and threshold animal models. Genetic correlations among parities were estimated by using two-trait linear–linear and single-trait random regression linear animal models. Genetic correlations with litter traits at birth were estimated by using a two-trait linear–linear animal model. Heritability estimates by linear model analysis were low (0.065–0.119 in Landrace & 0.061–0.157 in Large White); those by threshold model analysis were higher (0.136–0.200 & 0.110–0.283). Genetic correlations among parities differed between breeds and models. Genetic correlation between sow stayability and number born alive was positive in many cases, implying that selection for number born alive does not reduce sow stayability. The results seem to be affected by decisions on culling made by farmers.     

AN ACCELERATION SEARCH METHOD FOR UNCONSTRAINED OPTIMIZATION AND ITS APPLICATION IN MODEL PARAMETER ESTIMATION

In order to improve the convergence rate of the algorithms, an acceleration search method along a straight or curve is proposed,and the specific calculation steps of the algorithms are presented. The numerical results in model parameter estimation show that the convergence rate is improved and the calculation accords with the practical demands.     

Comparison between Calibration Procedure and Econometric Estimation

The two methods of estimating parameter in computable general equilibrium(CGE) model are introduced and compared:the calibration procedure and econometric estimation. The conclusions are:the estimation of parameter in CGE model must use the calibration procedure coupled with the econometric estimation method;the elasticity of output with respect to labor input,the marginal expenditure share for households and price elasticity of export demand are estimated by econometric estimation method;and other parameters of the CGE model can be get by calibration procedure.     

Approximate Estimate of Lateral Deflection for Rigid Frame and Frame-Shear Wall Structure Systems

This paper expounds the engineering significance of deliberating a method of approximate calculation,and has a discussion on lateral deflection of frame and frame_shear wall structures.     

Summarization of Current Research on Application of Durability of Structures

This paper summarized the recent research results about the durability of structures, introduced their current application in durability design, appraisal, estimation of rest life and strategy of maintenance and strengthening as well as in other fields.     

玉米苗枯病抗性鉴定方法的改进

采用玉米种子培养液对串珠镰刀菌分生孢子萌发抑制率和串珠镰刀菌毒素对玉米胚根、胚芽生长抑制率作为玉米苗枯病抗病鉴定指标,并与21个杂交玉米种苗枯病田间发病率进行相关分析来验证其准确性.结果表明,串珠镰刀菌毒素对玉米胚根、胚芽生长抑制率与玉米苗枯病田间发病率相关性较高,相关系数分别为0.925、0.919.该两种方法结果准确,可以作为玉米苗枯病抗性鉴定指标.     

Deep neural network algorithm for estimating maize biomass based on simulated Sentinel 2A vegetation indices and leaf area index

Accurate estimation of biomass is necessary for evaluating crop growth and predicting crop yield.Biomass is also a key trait in increasing grain yield by crop breeding.The aims of this study were(i)to identify the best vegetation indices for estimating maize biomass,(ii)to investigate the relationship between biomass and leaf area index(LAI)at several growth stages,and(iii)to evaluate a biomass model using measured vegetation indices or simulated vegetation indices of Sentinel 2A and LAI using a deep neural network(DNN)algorithm.The results showed that biomass was associated with all vegetation indices.The three-band water index(TBWI)was the best vegetation index for estimating biomass and the corresponding R2,RMSE,and RRMSE were 0.76,2.84 t ha−1,and 38.22%respectively.LAI was highly correlated with biomass(R2=0.89,RMSE=2.27 t ha−1,and RRMSE=30.55%).Estimated biomass based on 15 hyperspectral vegetation indices was in a high agreement with measured biomass using the DNN algorithm(R2=0.83,RMSE=1.96 t ha−1,and RRMSE=26.43%).Biomass estimation accuracy was further increased when LAI was combined with the 15 vegetation indices(R2=0.91,RMSE=1.49 t ha−1,and RRMSE=20.05%).Relationships between the hyperspectral vegetation indices and biomass differed from relationships between simulated Sentinel 2A vegetation indices and biomass.Biomass estimation from the hyperspectral vegetation indices was more accurate than that from the simulated Sentinel 2A vegetation indices(R2=0.87,RMSE=1.84 t ha−1,and RRMSE=24.76%).The DNN algorithm was effective in improving the estimation accuracy of biomass.It provides a guideline for estimating biomass of maize using remote sensing technology and the DNN algorithm in this region.