基于根方差法的MIS开发项目缓冲区研究

针对信息系统开发项目低成功率的特点,引入关键链,建立基于根方差法的项目关键链缓冲区模型,对缓冲区的设置与管理进行研究,改进传统的关键链缓冲区模型。算法求解上,设置信息系统开发项目工序的复杂度和资源紧张度两个调整参数,对缓冲区大小进行计算。最后,通过算例分析说明模型的实用性。

正态分布根方差的估计及其应用

用四分位极差的方法估计正态分布的根方差,研究了子样四分位极差及根方差估计的密度函数,并结合实例,说明了四分位极差估计具有稳健性.

正态分布中方差的稳健检验

对子样四分位极差和正态分布根方差估计量的密度函数进行了修正;通过模拟产生随机数据,利用基于四分位极差和子样方差估计而构造的检验统计量对正态分布的方差进行检验,结果说明了前者检验方法具有稳健性,且优于后者.

矩形超高层建筑横风向脉动风力.Ⅰ:基本特征

阐述系列论文的第一部分。对7个矩形截面超高层建筑模型进行了同步测压风洞试验。研究了横风向风力系数的根方差、功率谱密度、竖向相关性系数和相干函数的基本特征。通过对比不同厚宽比、不同风场的试验结果,研究了这两个参数对横风向脉动风力的影响效果。研究结果表明,厚宽比的影响效果最为显著,厚宽比不同,横风向脉动风力的作用机理可能也有所不同。

基于不确定性因素的柔性关键链缓冲设置方法

为了解决施工进度计划不具备柔性、实施过程中需根据实际进度不断调整变化等问题,在关键链项目管理中引入柔性技术,在其缓冲区设置时考虑实际进度控制中多种不确定性因素,从而提高了柔性关键链缓冲区设置的有效性。首先,基于柔性关键链技术,识别影响施工进度计划的内外部不确定性因素,并对这些不确定性因素进行评估和量化,在根方差法的基础上进行改进,提出了柔性关键链缓冲设置的新方法;然后,采用Monte Carlo模拟法对实例的计算结果的有效性进行验证,并计算出实例项目的完工率以及缓冲消耗情况;最后将新方法结果与C&PM,RSEM方法得到的结果进行对比分析。研究结果表明,这种基于多种不确定性因素的设置方法得到的柔性关键链缓冲更为合理、稳定和有效。

Vertical root distribution characters of Robinia pseudoacacia on the Loess Plateau in China

On the Loess Plateau, water is the main limiting factors for vegetation growth. Root distribution characters have special ecological meaning as it reflected the utilizations of trees to the environments. Even-aged stands ofRobinia pseudoacacia on slope lands facing south and north were selected as sampling plots for root distribution investigation. Investigatiing results showed that indicated that on all sites, root biomass decreased with depth, and the distribution depth of fine root was deeper than that of coarser root. The results of variance analysis indicated that there were great differences in root biomass among different diameter classes, and coarser root was the main sources of variance, and the root biomass, especially fine root (?<3mm) biomass on northern exposition sites was bigger than that on southern exposition sites. Analysis of the vertical root distribution parameters, root extinction coefficient, β indicated that the value of β on northern exposition was more than 0.982, while the value of β on southern exposition was less than 0.982, which indicated that the vertical root distribution depth ofRobinia pseudoacacia on southern exposition was deeper than that on southern exposition. And the distribution depth of fine roots (Φ<1mm) was deeper than that of thicker roots(Φ<3mm), which was in favor of the uptake of water and nutrients from deeper layers, helped the trees to adapt the arid environment, and promoted the growth of the upper parts of the tree. Keywords Root diameter classes - Variance analysis - Root extinction coefficient - Vertical distribution characters - Site conditions - Loess Plateau CLC number S792.27.01 Document code A Foundation Item: This research was supported by National Natural Science Foundation of China (30371150 and 40371075).Biography: LI Peng (1974-) male, post: Ph. D. in Northwest Scientific & Technological University of Agriculture and Forestry, Yangling 712100, Shaanxi Province, P. R. China. Tel: 029-82312651.Responsible editor: Chai Ruihal

基于关键链技术的施工项目管理进度研究

结合恒逸(文莱)PMB石油化工项目,综合项目总体施工方案、施工难点及项目进度目标的影响因素,基于关键链的项目进度管理技术,对工作的持续时间进行了优化。其中包括了活动时间的估计、项目的工作分解、约束资源及关键链的确定和缓冲区设置等内容,实际成果表明:运用关键链技术能够有效节约工期,该方法值得推广。

关键链进度控制中缓冲区设置修正研究——以上海国际金融中心项目为案例

关键链中缓冲区设置的常用方法——根方差法,在应用于复杂性、不确定性较高的大型复杂项目时需要修正设置。根据大型复杂项目的特性,引进修正因素资源约束程度、工序复杂程度、不确定性、工序持续时间比例、工序位置系数和管理者的风险偏好,对根方差法进行修正,以实现根方差法在大型复杂项目的缓冲区设置的顺利运用。方法在上海国际金融中心项目建设中得到了验证。

山区某大跨叠合梁斜拉桥静阵风荷载及抖振响应研究

为探究山区某大跨叠合梁斜拉桥成桥态和最大单悬臂施工态下的静阵风荷载及抖振响应,首先采用通用有限元软件ANSYS建立其三维空间有限元模型,其次基于谐波合成法和准定常理论得到三维脉动风场,最后基于Davenport理论和Scanlan颤抖振理论,采用数值模拟法探究了山区某大跨叠合梁斜拉桥静阵风荷载及抖振响应规律。主要得出以下结论:顺桥向静阵风荷载下最大单悬臂施工态侧向位移最大值为0.96m,且主梁截面的内力随主梁到桥塔距离减小而增加;成桥态下静阵风响应规律与最大单悬臂施工态下保持一致,但在顺桥向荷载下的施工态弯矩值要大于成桥态弯矩值,最大相差19.69倍;成桥态和最大单悬臂状态下主梁跨中位置的位移响应根方差最大值分别为0.052m和0.095m。

A Model for Estimating Total Forest Coverage with Ground-Based Digital Photography

Vegetation fractional coverage (VFC) is one of the key indicators of vegetation distribution. In the work a measurement-based model was developed to derive total forest VFC (TG) as well as the VFC of trees (T) and shrub-grasses (G) separately in a subtropical forest area in Nanjing, China. Both upward and downward photographs were taken with a digital camera in 72 quadrats (10 m × 10 m each). Fifteen models were established and validated. Models jointly using both T and G performed better than those using the T and G separately. The best model, TG = T + G- 1.134 × T × G- 0.025 (R2 = 0.9115, P < 0.01, root mean squared error = 0.0789), is recommended for application. This model provides a good way to obtain total forest VFC values through taking tree and shrub-grass photos on ground below tree canopy rather than above tree canopy.

Validation and intercomparison of HY-2A/MetOp-A/Oceansat-2 scatterometer wind products

Sea surface winds are of great significance in scientific research. In the last few years,three series of scatterometers were launched to measure these winds,including the Advanced Scatterometer(ASCAT) aboard Meteorological Operational Satellite A(Met Op-A) and Met Op-B,Oceansat-2 Scatterometer(OSCAT),and HY-2A Scatterometer(HY-2A SCAT). Based on buoy wind data,validation and intercomparison of these scatterometers were performed. Scatterometer-derived wind and buoy wind data were collected only if the spatial difference was less than 0.1 degree and temporal difference less than 5 min. After discarding wind direction data outside five times the standard deviation,ASCAT wind products showed high accuracy in both wind speed and direction,with root-mean-square error(RMSE) 0.86 m/s and 17.97 degrees,respectively. HY-2A SCAT nearly meets the mission requirement,with RMSE for wind speed 1.23 m/s and 22.85 degrees for wind direction. OSCAT had poor performance when compared with the others. RMSE for wind speed was 1.54 m/s and 39.86 degrees for wind direction,which greatly exceeds the mission requirement of 20 degrees. In addition,the RMSE for wind direction shows a high-low pattern on buoy wind speed. However,a wind speed range from 14 to 15 m/s was found to be abnormal,and the reason remains unclear. There was no systematic dependency of both wind speed and direction residuals on buoy wind speed and cross-track location of the wind vector cells across the entire range. No seasonal variation was found for any scatterometer.

Estimating van Genuchten Model Parameters of Undisturbed Soils Using an Integral Method

The van Genuchten model is the most widely used soil water retention curve （SWRC） model. Two undisturbed soils （clay and loam） were used to evaluate the accuracy of the integral method to estimate van Genuchten model parameters and to determine SWRCs of undisturbed soils. SWRCs calculated by the integral method were compared with those measured by a high speed centrifuge technique. The accuracy of the calculated results was evaluated graphically, as well as by root mean square error （RMSE）, normalized root mean square error （NRMSE） and Willmott＇s index of agreement （1）. The results obtained from the integral method were quite similar to those by the centrifuge technique. The RMSEs （4.61 ×10^-5 for Eum-Orthic Anthrosol and 2.74 × 10^-4 for Los-Orthic Entisol） and NRMSEs （1.56 × 10^-4 for Eum- Orthic Anthrosol and 1.45 ×10^-3 for Los-Orthic Entisol） were relatively small. The 1 values were 0.973 and 0.943 for Eum-Orthic Anthrosol and Los-Orthic Entisol, respectively, indicating a good agreement between the integral method values and the centrifuge values. Therefore, the integral method could be used to estimate SWRCs of undisturbed clay and loam soils.

Comparison of six statistical approaches in the selection of appropriate fish growth models

The performance of six statistical approaches,which can be used for selection of the best model to describe the growth of individual fish,was analyzed using simulated and real length-at-age data.The six approaches include coefficient of determination(R2),adjusted coefficient of determination(adj.-R2),root mean squared error(RMSE),Akaike's information criterion(AIC),bias correction of AIC(AICc) and Bayesian information criterion(BIC).The simulation data were generated by five growth models with different numbers of parameters.Four sets of real data were taken from the literature.The parameters in each of the five growth models were estimated using the maximum likelihood method under the assumption of the additive error structure for the data.The best supported model by the data was identified using each of the six approaches.The results show that R2 and RMSE have the same properties and perform worst.The sample size has an effect on the performance of adj.-R2,AIC,AICc and BIC.Adj.-R2 does better in small samples than in large samples.AIC is not suitable to use in small samples and tends to select more complex model when the sample size becomes large.AICc and BIC have best performance in small and large sample cases,respectively.Use of AICc or BIC is recommended for selection of fish growth model according to the size of the length-at-age data.

Comparative Analysis of Four Stem Taper Models for Quercus glauca in Mount Halla,Jeju Island,South Korea

This study was conducted to fit the diameter-height data of Quercusglaucain Jeju Island, South Korea to the four commonly used stem taper equations andto evaluate the performance of the four stem taper models using four statistical criteria： Fit index （FI）, root mean square error （RMSE）, bias （）,and absolute mean difference （AMD）. Results showed that the Kozak02stem taper equation provided the best FI（0.9847）, RMSE（1.5745）,（-0.0030 cm） and AMD （1.0990 cm） whileMax and Burkhart model had the poorest performance among the four stem taper models based on the four evaluation statistics （FI ： 0.9793,RMSE ： 1.8272, ： 0.3040 cm and AMD ： 1.3060 cm）. These stem taper equations can serve as a useful tool for forest managers in estimating the diameter outside bark at any given height, merchantable stem volumes and total stem volumesof the standing trees of Quercusglaucain theGotjawal forests located in Mount Halla, Jeju Island, South Korea.

Slope displacement prediction based on morphological filtering

Combining mathematical morphology (MM),nonparametric and nonlinear model,a novel approach for predicting slope displacement was developed to improve the prediction accuracy.A parallel-composed morphological filter with multiple structure elements was designed to process measured displacement time series with adaptive multi-scale decoupling.Whereafter,functional-coefficient auto regressive (FAR) models were established for the random subsequences.Meanwhile,the trend subsequence was processed by least squares support vector machine (LSSVM) algorithm.Finally,extrapolation results obtained were superposed to get the ultimate prediction result.Case study and comparative analysis demonstrate that the presented method can optimize training samples and show a good nonlinear predicting performance with low risk of choosing wrong algorithms.Mean absolute percentage error (MAPE) and root mean square error (RMSE) of the MM-FAR&LSSVM predicting results are as low as 1.670% and 0.172 mm,respectively,which means that the prediction accuracy are improved significantly.

3-D reconstruction of coastal bathymetry from AIRSAR/POLSAR data

This paper introduces a new method for reconstructing three-dimensional （3D） coastal bathymetry changes from Airborne AIRSAR/POLSAR synthetic aperture data. The new method is based on integration between fuzzy B-spline and Volterra algorithm. Volterra algorithm is used to simulate the ocean surface current from AIRSAR/POLSAR data. Then, the ocean surface current information used as input for continuity equation to estimate the water depths from AIRSAR/POLSAR data. This study shows that 3D ocean bathymetry can be reconstructed from AIRSAR/POLSAR data with root mean square error of ±0.03 m.

Satellite derived upper ocean thermal structure and its application to tropical cyclone intensity forecasting in the Indian Ocean

Upper ocean heat content is a factor critical to the intensity change of tropical cyclones(TCs). Because of the inhomogeneity of in situ observations in the North Indian Ocean,gridded temperature/salinity(T/S) profiles were derived from satellite data for 1993–2012 using a linear regression method. The satellite derived T/S dataset covered the region of 10°S–32°N,25°–100°E with daily temporal resolution,0.25°×0.25° spatial resolution,and 26 vertical layers from the sea surface to a depth of 1 000 m at standard layers. Independent Global Temperature Salinity Profile Project data were used to validate the satellite derived T/S fields. The analysis confirmed that the satellite derived temperature field represented the characteristics and vertical structure of the temperature field well. The results demonstrated that the vertically averaged root mean square error of the temperature was 0.83 in the upper 1 000 m and the corresponding correlation coefficient was 0.87,which accounted for 76% of the observed variance. After verification of the satellite derived T/S dataset,the TC heat potential(TCHP) was verified. The results show that the satellite derived values were coherent with observed TCHP data with a correlation coefficient of 0.86 and statistical significance at the 99% confidence level. The intensity change of TC Gonu during a period of rapid intensification was studied using satellite derived TCHP data. A delayed effect of the TCHP was found in relation to the intensity change of Gonu,suggesting a lag feature in the response of the inner core of the TC to the ocean.

Evaluation of Total Precipitable Water over East Asia from FY-3A/VIRR Infrared Radiances

Satellite retrieval of atmospheric water vapor is intended to further understand the role played by the energy and water cycle to determine the Earth's weather and climate.The algorithm for operational retrieval of total precipitable water (TPW) from the visible and infrared radiometer (VIRR) onboard Fengyun 3A (FY-3A) employs a split window technique for clear sky radiances over land and oceans during both day and night.The retrieved TPW is compared with that from the moderate resolution imaging spectroradiometer (MODIS) onboard the Terra satellite and data from radiosonde observations (RAOB).During the study period,comparisons show that the FY-3A TPW is in general agreement with the gradients and distributions from the Terra TPW.Their zonal mean difference over East Asia is smaller in the daytime than at night,and the main difference occurs in the complex terrain at mid latitude near 30°N.Compared with RAOB,the zonal FY-3A and the Terra TPW have a moist bias at low latitudes and a dry bias at mid and high latitudes;in addition,the FY-3A TPW performs slightly better in zonal mean biases and the diurnal cycle.The temporal variation of the FY-3A and the Terra TPW generally fits the RAOB TPW with the FY-3A more accurate at night while Terra TPW more accurate during the daytime.Comparisons of correlations,root mean square differences and standard deviations indicate that the FY-3A TPW series is more consistent with the RAOB TPW at selected stations.As a result,the FY-3A TPW has some advantages over East Asia in both spatial and temporal dimensions.

Prediction of representative deformation modulus of longwall panel roof rock strata using Mamdani fuzzy system

Deformation modulus is the important parameter in stability analysis of tunnels, dams and mining struc- tures. In this paper, two predictive models including Mamdani fuzzy system （MFS） and multivariable regression analysis （MVRA） were developed to predict deformation modulus based on data obtained from dilatometer tests carried out in Bakhtiary dam site and additional data collected from longwall coal mines. Models inputs were considered to be rock quality designation, overburden height, weathering, unconfined compressive strength, bedding inclination to core axis, joint roughness coefficient and fill thickness. To control the models performance, calculating indices such as root mean square error （RMSE）, variance account for （VAF） and determination coefficient （R^2） were used. The MFS results show the significant prediction accuracy along with high performance compared to MVRA results. Finally, the sensitivity analysis of MFS results shows that the most and the least effective parameters on deformation modulus are weatherin~ and overburden height, respectively.

Establishment and tests of EnOI assimilation module for WAVEWATCH Ⅲ

In this paper, we propose a parallel data assimilation module based on ensemble optimal interpolation （EnOI）. We embedded the method into the full-spectral third-generation wind-wave model, WAVEWATCH III Version 3.14, producing a wave data assimilation system. We present our preliminary experiments assimilating altimeter significant wave heights （SWH） using the EnOI-based wave assimilation system. Waters north of 15°S in the Indian Ocean and South China Sea were chosen as the target computational domain, which was two-way nested into the global implementation of the WAVEWATCH III. The wave model was forced by six-hourly ocean surface wind velocities from the cross-calibrated multi-platform wind vector dataset. The assimilation used along-track SWH data from the Jason-2 altimeter. We evaluated the effect of the assimilation on the analyses and hindcasts, and found that our technique was effective. Although there was a considerable mean bias in the control SWHs, a month-long consecutive assimilation reduced the bias by approximately 84% and the root mean-square error （RMSE） by approximately 65%. Improvements in the SWH RMSE for both the analysis and hindcast periods were more significant in July than January, because of the monsoon climate. The improvement in model skill persisted for up to 48 h in July. Furthermore, the SWH data assimilation had the greatest impact in areas and seasons where and when the sea-states were dominated by swells.