落叶松人工林直径分布动态预估模型1）

基于小兴安岭地区和长白山地区102块落叶松人工纯林固定标准地复测数据（10 a间隔期）,采用参数预测模型（PPM）系统,建立了前期Weibull分布参数（b1）与前期林分调查因子模型、前期参数c1与b1之间的回归模型、两期参数b2与b1的回归模型、以及两期参数c2与b2之间的回归模型,并采用似乎不相关回归（ SUR）理论,估计了模型的参数;利用“刀切法”选择平均相对误差（ ME ）、平均相对误差绝对值（ MAE ）、预测精度（ P）、相对误差（ B）、误差指数（ IE ）等指标,分别对所建立的参数动态预测方程及直径分布动态预测结果进行了检验。结果表明：所有模型的R2a较好（0．428～0．897）,RMSE均较小（0．37～0．94）,所建立的直径分布动态预测模型具有较好的拟合效果。通过检验,所建立的参数动态模型预估能力较好（－10％＜ME＜－2％,P＞95％）,并能较好地预测落叶松人工林未来直径分布（B0＝4．38％,B1＝12．38％,IE＝524）。     

Tree improvement effects on tree size distributions for Picea glauca and Picea mariana in New Brunswick,Canada

Abstract

Height and diameter distributions between improved and unimproved (checklot) seedlots for white spruce [Picea glauca (Moench) Voss] and black spruce [Picea mariana (Mill.) BSP] were compared using the two-parameter Weibull function. Individual tree height at age 5–15 years and diameter at breast height at age 15 years that were collected from two series of large-plot realized gain tests were used for this purpose. For both species, improved seedlots did not significantly (α=0.05) change the shape parameter of the distributions relative to their checklots, suggesting that an overall shape value will be adequate to predict tree size distributions of various improved seedlots. The most important finding was that seedlot influenced the scale parameter (related to the range of the distribution) significantly, but from a practical viewpoint, only those scale values of the higher rated seedlots (i.e. seedlots collected from a rogued seed orchard or superior families) were significantly higher (α=0.05) than those of the respective unimproved seedlot. The changes in scale value of the alternative improved seedlots relative to the checklot (Δ_Scale) were comparable in magnitude to the respective realized genetic gains, suggesting that tree improvement effects on the scale value can be adjusted by realized genetic gains. The results also suggest that site and age significantly affected the scale value; in general, Δ_Scale became larger at earlier ages or on better sites. The findings reported here will be used in the development of yield functions for genetically improved white and black spruce in New Brunswick.     

威布尔(Weibull)空间分布型模型的抽样式研究

本文首次运用威布尔分布于昆虫空间分布型的抽样式研究中,经推导得出符合威布尔分布型模型的理论抽样式和序贯抽样式,具体给出了惠安县马尾松毛虫种群的抽样规则,旨在为实际应用和进一步研究提供科学依据。     

Reliability model for Subsystems of CNC machine tool with small samples

Many subsystems in CNC machine tool have only a few failures, so they are small samples. In this case, classical reliability modeling method often has large errors. For the failure data of small sample, maximum likelihood estimation method is used to estimate the Weibull distribution model parameters of time between failures of the subsystems. Then, the Weibull distribution model parameters are modified by parameter bias correction method. Finally, the effect of bias correction parametersis tested by the D test and the error area ratio test method. The test results show that the modified models are better.     

光肩星天牛幼虫空间分布型的研究

本文采用扩散系数Ｃ法、扩散指数Ｉ０法、Ｃａｓｓｉｃ指标ＣＡ法，种群群集均数入法，Ｔａｙｌｏ指数ｂ法和Ｉｗａｏ的平均拥挤度ｍ与平均数ｘ的回归分析法，测定了杨树上光肩星天牛幼虫的空间分布属于聚集分布，符合负二项分布模型。同时探讨了空间分布型在序贯抽样中的应用。行道树和防护林中理论取样数（Ｎ）与单株虫口平均密度（ｘ－）的关系分别为：Ｎ＝８．００利用有虫株率（Ｐ）简易估计虫口密度的关系式分别为：ｘ＝７．２６２０［－／ｎ（１一Ｐ）］￣０．６００３和ｘ＝３．６９２５［－１ｎ（１－Ｐ）］￣．３９１０１。     

基于夭折试验样本寿命分布的参数估计

研究了在夭折试验样本下指数分布与威布尔分布的参数估计问题。     

Optimal preventive maintenance interval period of CNC

On the basis of failure data gathered from 5 NC machine tools of one type in one year,a two-parameter Weibull distribution model is established,and this model has passed linear correlation test and hypothesis testing. On the principle of the most effectiveness,the best preventive maintenance intervals model on the state of reparative maintenance is brought forward,and the best preventive maintenance intervals of this type have been calculated. In the end,an appropriate maintenance plan is brought forward according to the best preventive maintenance intervals,and the maintenance cost is greatly reduced and the availability of this type of NC machine tool are kept at the same time.     

辽东山区天然次生林林分直径分布模型研究

以峰度、偏度和变动系数为指标研究了辽东山区天然次生林直径株数分布特征。运用Johnson’s SB分布、Gamma分布、3参数和2参数Weibull分布等4种概率密度函数研究了辽东山区天然次生林直径株数分布规律,同时利用Kolmogorov-Smirnov(KS)检验法来检验4种概率分布的拟合效果,结果表明:林分直径的株数分布以Johnson’s SB分布拟合效果最好,Weibull分布(包括2参数和3参数)仅仅适合中度区和弱度区,但不是最好。所有的分布模型均通过了优势度检验,说明均适用于直径株数分布的拟合。     

青石冈林场木荷直径结构研究

以湖南青石冈林场木荷人工林为研究对象,分析了木荷直径结构规律。运用威布尔分布(Weibull)、正态分布、对数正态分布和伽马(Gamma)分布进行直径拟合,并结合X2对拟合结果进行检验,结果表明:木荷林分平均胸径为10.4cm,在5.1～37.1cm之间变动,全距32.0cm,径阶分布范围不大;小径阶的林木数量居多(6～12cm),累计百分比已达到83.7%;4种分布函数中,威布尔分布拟合效果最好,其次是对数正态分布,但两者的差异不大,均可用于预测木荷林直径结构。     

林分直径结构的Weibull研究——以日本落叶松为例

日本落叶松直径服从Weibull分布,本研究编制了直径分布预估概率表;其形状参数C取不同的值时,其分布曲线形状类型即不同,当1.8相似文献