Performance of DSSAT-Nwheat across a wide range of current and future growing conditions

Crop models are widely used in agricultural impact studies. However, many studies have reported large uncertainties from single-model-based simulation analyses, suggesting the need for multi-model simulation capabilities. In this study, the APSIM-Nwheat model was integrated into the Decision Support System for Agro-technology (DSSAT), which already includes two wheat models, to create multi-model simulation capabilities for wheat cropping systems analysis. The new model in DSSAT (DSSAT-Nwheat) was evaluated using more than 1000 observations from field experiments of 65 treatments, which included a wide range of nitrogen fertilizer applications, water supply (irrigation and rainout shelter), planting dates, elevated atmospheric CO₂ concentrations, temperature variations, cultivars, and soil types in diverse climatic regions that represented the main wheat growing areas of the world.DSSAT-Nwheat reproduced the observed grain yields well with an overall root mean square deviation (RMSD) of 0.89 t/ha (13%). Nitrogen applications, water supply, and planting dates had large effects on observed biomass and grain yields, and the model reproduced these crop responses well. Crop total biomass and nitrogen uptake were reproduced well despite relatively poor simulations of observed leaf area measurements during the growing season. The low sensitivity of biomass simulations to poor simulations of leaf area index (LAI) were due to little changes in intercepted solar radiation at LAI >3 and water and nitrogen stress often limiting photosynthesis and growth rather than light interception at low LAI.The responses of DSSAT-Nwheat to temperature variations and elevated atmospheric CO₂ concentrations were close to observed responses. When compared with the two other DSSAT-wheat models (CERES and CROPSIM), these responses were similar, except for the responses to hot environments, due to different approaches in modeling heat stress effects.The comprehensive evaluation of the DSSAT-Nwheat model with field measurements, including a comparison with two other DSSAT-wheat models, created a multi-model simulation platform that allows the quantification of model uncertainties in wheat impact assessments.     

E－凸集的几个基本性质

利用比较与分析的方法，由E-凸集的定义出发，研究了E-凸集的若干基本性质．所得结果丰富并深化了凸分析的基本内容，拓宽了广义凸性在优化理论及其应用中的研究范围．     

Application of Attribute Reduct Method in Spatial Load Forecasting

Spatial load forecasting is a process distributing the total forecasted load to all partitioned area, and involving more spatial information and more factor influencing application of the future small area, which need a great deal of memory space and longer operation time. Rough set is new method of data analysis. It need not be provided with any advanced information except data set. But attribute reduct is its main algorithms. Division matrix approach on rough set used to reduce the attribute related to land - use decision in order to remove redundancy attribute and then the rules of small area land - use decision is distilled. The method obtained better effect and enhanced the total load forecasting efficiency.     

New Algorithms for Data Discretization Based on Rough Set Theory

The discretization of real values is always one of the key problems to be solved in the domain of machine learning for its great contribution to speeding up the followed learning algorithms, cutting down the real demand of algorithms on running space and time, and improving the clustering capability of the ultimate learning results. The basic characteristics and framework of discretization approaches based on rough set model are analyzed at first, then the different measurements of the importance of candidate cuts are discussed and researched. Two new heuristic algorithms are put forward to finally select the useful cuts from a candidate set. The selected cuts of the two algorithms will adequately maintain the discernible relation of information systems for their full considering the specialty of rough set, which perfectly embodies the advantages of this theory. Moreover, excellent discretization results may be expected through these heuristic algorithms.     

Determination to Weighting Coefficient of Combination Forecast Based on Rough Set Theory

The problem of determination to weighting coefficient is a key and difficulty for combination forecast. A method of determining weighting coefficient based on rough set theory is showed in this paper. Determining weighting coefficient is translated into estimating significance of attributes among rough set. A relation data model about combination forecast is established. Knowledge systems are built through making attribute value into eigenvalue. Under data moving, the weighting coefficients of a combination forecast model are computed by analyzing the dependence and significance of forecasting method for the predicted object. The proposed approach overcomes the subjectivity of traditional determination to weighting coefficient, avoids computing linear or nonlinear extremum problem and makes combination forecast more objective. The validity of the proposed approach is verified with a case.     

A Method of Analyzing the Parameter Sensitivity of Large Rotor Systems and Its Application

Based upon the eigenvalue sensitivity theory of non-self-adjoit system and the component mode synthesis method,a new technique is developed to analyze the eigenvalue sensitivity to variation of parameters of large rotor-bearing system. As an application, the influence of the journal bearing parameters on the stability of a large domestic turbine-generator set is analyzed and discussed.     

日本稻谷干燥机械化发展研究

日本稻谷干燥机械化程度已达到95%以上.在日本,水稻收割后实施产地及时烘干贮藏,大米品质好,米价高出我国10倍.我国稻谷干燥机械化程度低,干燥机械普及率低,直接影响稻谷生产效益和在国际市场的竞争力.借鉴日本成功的稻谷干燥机械化发展经验,推广和普及稻谷干燥设备,是我国农业生产中亟待解决的问题.     

烟草成分对其品质影响程度的粗糙集判别方法

运用粗糙集理论研究了烟草主要化学成分 (总糖、还原糖、总氮、烟碱、氧化钾和氯离子 )对烟草品质影响程度的判别方法。对比已有的研究结果 ,表明基于粗糙集理论的计算方法简单 ,结果明了 ,而且还能量化烟草成分对品质的影响程度。     

基于灰色关联分析的区域保险差异影响因素分析

研究了经济学中广泛应用的决策模糊理论中模糊集覆盖系数的性质，并据此提出了无须通过繁杂的统计实验就能够计算覆盖系数的实用方法，进而提出了模糊集交并运算算子. 用两个算例说明了该方法和算子与实际情形相符，具有可行性.     

伐区作业类型划分与集材作业系统相适应性的研究

本应用模糊聚类分析方法,选取作业区坡度、单位面积出材量、集材距离以及地表承载能力等作为因子,对吉林林区伐区作业类型进行了区划。又应用层次分析法,对与每类伐区相适应的集材作用系统进行系统分析。