基于线性规划模型的农业种植业结构优化研究

以土地资源、农作物需水量、肥料、乡村劳动力资源、农业机械总动力等作为农业种植业规划的约束条件,建立基于线性规划的农业种植业结构优化数学模型。以山东枣庄市为例,提出农业种植业结构优化方案,该优化方案具有实用性和合理性。     

BP神经网络在静力触探确定单桩承载力中的应用

运用BP神经网络建立了静力触探成果与单桩承载力的相关关系，并通过工程实例将BP神经网络预报值与线性回归数学模型、规范公式方法计算值进行对比，说明BP神经网络在利用静力触探成果确定单桩承载力中是一种行之有效的方法，具有精度高，信息处理智能化等特点，计算结果明显优于传统的线性回归数学模型和规范公式方法，具有较好的应用价值。     

粮食产后系统评判方法的探讨

本文根据我国南方粮食产后系统的现状和特点,建立了产后系统多层次、多目标评判模型,并提出以产后处理损失、处理成本投入、系统处理效率和粮食品质变化等四个参数为系统评判的指标体系,对浙江省现行三种系统模式进行了综合评判,较全面地分析比较了各模式的性能,明确了适用条件和薄弱环节,为合理选用和改进完善粮食产后系统提供了依据。     

直接进给机构摩擦力特性研究

以直线电机驱动的直接进给机构为研究对象,进行直接进给机构摩擦力特性分析。搭建了直接进给机构摩擦力测试实验平台,采用激光干涉仪和高频电流传感器等设备进行位移和电流数据收集,进行数据处理;得到摩擦力与位移、摩擦力与速度的关系,建立摩擦力特性模型。结果表明,预滑动阶段,摩擦力存在明显的迟滞现象,且摩擦力随进给速度的增加呈线性增长,增长过程中摩擦力表现为粘滞摩擦。为直线进给机构摩擦情况的研究提供了支持和参考。     

基于土壤-作物系统模拟模型的冬小麦田间水氮优化管理

将作物生长模型与土壤水氮管理过程模块相结合,构建了土壤-作物系统水分养分模拟模型。以灌水、施氮总量为决策变量,冬小麦生物量、水分和氮肥利用效率为优化目标,将冬小麦按生长发育时期分为6个阶段,建立了多目标的动态规划模型。在土壤-作物系统过程模型的基础上,用动态规划的方法对田间水、氮资源管理措施进行优化。通过对作物水分胁迫系数和氮肥胁迫系数的模拟计算,可获得最佳的灌水、施肥时间及用量。算例结果表明：在养分供应充足仅水分胁迫的条件下,优化方案的灌水量较对照处理平均节约了25%,水分利用效率比对照处理平均高出约1     

单纯形—正反步长优化方法（SSPSS）及其在农业上的应用

本文提出了一种新的多变量有约束非线性函数的寻优方法——单纯形一正反步长法(SSPSS)。文中详细阐述了该方法的搜索策略和具体步骤。同时,通过实例比较了相对步长模拟法的优点。     

利用广义线性模型预测家畜离散性状育种值

将广义线性混合模型(GLMM)引入动物离散性状的遗传分析及个体的遗传评定,初步比较了GLMM方法与一般线性方法(LM)的估计效果。模拟研究的性状为单阈值二项分类性状,选用的连接函数为对数连接μi=eη/(1+eη),方差函数为V(μi)=μ(i1-μi)/n,试验设计为全同胞-半同胞混合家系,参数估计采用Fisher迹法。结果表明:GLMM方法能较准确地估计公畜的个体育种值,在个体的遗传评定效果方面要明显优于常规的线性方法,其预测的育种值排序结果与真实育种值的排序之间存在极显著的相关性(P<0.001)。     

Comparing multipurpose forest management with timber management,incorporating timber,carbon and oxygen values: A case study

Abstract

This paper comparatively examines two forest management planning approaches: multipurpose forest management and traditional timber management, with carbon, timber and oxygen production objectives in mind. The effects of both approaches on carbon and oxygen values were estimated with an oxygen and carbon flow matrix, while timber production was modelled through a growth and yield model. The estimated values were simultaneously integrated into a linear programming model developed for this study. The objective was to maximize the net present value (NPV) of the profits of timber, oxygen and carbon under the constraints of an even flow of timber production and ending forest inventory for each planning approach. The results showed that the ecological and environmental regulations in multipurpose management substantially decreased the NPV of timber production even though they increased the NPV of carbon and oxygen flow. The results also indicated that over a 100 year planning horizon the total NPV of all forest ecosystem values including carbon, timber and oxygen is almost the same (only 1.9% reduction in multipurpose management approach) in both management approaches. Although multipurpose management creates more NPV of carbon and oxygen than timber management does, the latter provides better results in terms of timber production. It is therefore important to take into account the NPV of all apparent and quantifiable forest values in preparing forest management plans, particularly in developing new management planning approaches.     

Development of a linear mixed-effects individual-tree basal area increment model for masson pine in Hunan Province,South-central China

ABSTRACT

An individual-tree basal area increment model was developed for masson pine based on 26276 observations of 13,138 trees in 987 sample plots from the 7th (2004), 8th (2009), and 9th (2014) Chinese National Forest Inventory in Hunan Province, South-central China. The model was built using a linear mixed-effects approach with sample plots included as random effects since the data have a hierarchical stochastic structure and biased estimates of the standard error of parameter estimates could be a consequence of applying ordinary least square (OLS) for regression. In addition, within-plot heteroscedasticity and autocorrelation were also considered. The final mixed-effects model was determined according to the Akaike information criterion (AIC), Bayesian information criterion (BIC), log-likelihood (Loglik), and the likelihoodratio test (LRT). The results revealed that initial diameter (DBH), the sum of the basal area (m²/ha) in trees with DBHs larger than the DBH of the subject tree (BAL), number of trees per hectare (NT), and elevation (EL) had a significant impact on individual-tree basal area increment. The mixed-effects model performed much better than the basic model produced using OLS. Additionally, the variance structure of the model errors was successfully modeled using the power function. However, the autocorrelation structures were not defined because there was no autocorrelation amongst the data. It is believed that the final model will contribute to the scientific management of the masson pine.     

Application of the Tweedie distribution to zero-catch data in CPUE analysis

We focus on the zero-catch problem of CPUE (catch per unit effort) standardization. Because the traditional CPUE model with a log-normal error structure cannot be applied in this case, three methods have often been utilized as follows:

(1) Ad hoc method adds a small constant value to all response variables.

(2) Catch model with a Poisson or negative-binomial (NB) error structure.

(3) Delta-type two-step method such as the delta-normal model (after estimating the ratio of zero-catch using a logit or probit model, a model such as CPUE log-normal or Catch-Poisson is applied to CPUE without zero-data).

However, there are some statistical problems with each of these methods.In this paper, we carried out the CPUE standardization mainly using the Tweedie distribution model based on the actual by-catch data (silky shark, Carcharhimus falciformis, in the North Pacific Ocean caught by Japanese training vessels) including many observations with zero-catch (>2/3rd) and tuna fishery data as a target (yellowfin tuna, Thunnus albacares, in the Indian Ocean caught by Japanese commercial vessels) where the ratio of zero-catch is not so high (<1/3rd). The Tweedie model is an extension of compound Poisson model derived from the stochastic process where the weight of the counted objects (i.e., number of fish) has a gamma distribution and has an advantage of handling the zero-catch data in a unified way.We also compared four candidate models, the Catch-NB model, ad hoc method, Delta-lognormal model (delta-type two-step method) and Tweedie distribution, through CPUE analyses of actual fishery data in terms of the statistical performance. Square error and Pearson's correlation coefficient were calculated based on the observed CPUE and the corresponding predicted CPUE using the n-fold cross-validation.As a result, the differences in the trend of CPUE between years and model performance between the ad hoc method and Tweedie model were found to be not so large in the example of yellowfin tuna (target species). However, the statistical performance of Tweedie distribution is rather better than Delta-lognormal model, the Catch-NB distribution and ad hoc method in the example of silky shark (by-catch species). Standardized CPUE year trend of ad hoc method was found to be quite different from that of the Tweedie distribution and other two models. Model performance of the Tweedie distribution is good judging from the 5-fold cross-validation using the fishery data if including many zero-catch data such as by-catch species.