磷化工企业计划模型及其算法研究

磷化工企业计划决策问题非常复杂,涉及的因素非常之多,是一个有待深入研究的领域.本文构建了磷化工企业的计划决策大型线性目标规划模型,该模型分采矿模块、选矿模块、制肥和销售以及综合目标5个模块,同时,提出了求解该模型的有界变量后分析法.实例计算表明,提出的模型和方法可靠实用,有助于企业制定一个优化的计划.     

不确定大时延下遥操作对象模型的在线修正方法

基于预测模型的遥操作是消减通信大时延的有效方法,预测精度直接影响操作品质。分析了遥操作中的不确定大时延及有限带宽对模型修正的影响,针对模型参数的不确定性,提出了一种新的模型在线修正方法。该方法采用时标标识、同态模型、数据平滑等策略,有效克服了实测信息错配、反馈修正与实时预测过程异步以及变采样步长问题,实现了模型的精确在线修正,提高了预测精度和系统的鲁棒性。通过仿真实验验证了该方法的有效性。     

不确定性结构区间分析的改进Monte Carlo方法

将结构系统中的不确定性参数用区间数来表示，建立了系统的区间有限元控制方程。利用Monte Carlo数值仿真方法对区间有限元控制方程进行求解，得到了结构的位移和应力响应区间。并针对—殷Monte Carlo方法在区间仿真中存在的缺陷，对其进行了改进，使其计算效率大为提高．数值仿真算例表明：经改进的Monte Carlo方法仿真求解计算量大为减少，且能给出较高精度的响应区间，并克服了区间运算中的扩张问题。     

阵列天线通道不一致性校正的辅加阵元法

MUSIC算法是一种基于特征值分解的超分辨DOA估计算法,在理想阵列条件下,其估计性能良好,但当信号模型与实际信号环境不匹配,即存在系统误差时,MUSIC算法的估计性能会严重下降,甚至失效。针对模型中普遍存在的通道不一致性误差,本文首先分析了此类误差对测向性能的影响,并提出了一种通道误差校正的简易算法,该方法通过对来自辅加阵元信号的数据信息进行处理,获取通道不一致性误差的估计,通过误差补偿有效地抑制了通道不一致性的影响,提高了DOA估计的性能。给出了应用该方法的具体步骤,计算机仿真结果证明了该算法的有效性。     

Best Tracking Performance under Plant Uncertainty and Control Energy Constraint

This paper has investigated best tracking performance for linear feedback control systems in the case that plant uncertainty and control effort need to be considered simultaneously. Firstly, an average integral square criterion of the tracking error and the plant input energy over a class of additive model errors is defined. Then, utilizing spectral factorization to minimize the performance index, we obtain an optimal controller design method, and furthermore study optimal tracking performance under plant uncertainty and control energy constraint. The results can be used to evaluate optimal average tracking performance and control energy in designing practical control systems.     

非高斯型互相关随机数的发生技术

在用蒙特卡罗法进行仿真研究（例如进行测量不确定度评定）时,常常需要发生多个非高斯型互相关的随机数.就这一问题,给出完整的解决方案：用Hermite展开式生成近似的非高斯变量,借助Cholesky分解建立各变量之间的相关性.方法的关键在于对互相关系数矩阵进行“预变形”,使Cholesky分解也适用于非高斯变量.此外,还利用Cholesky分解式下三角矩阵的特点,对矩调整和建立相关性两个过程进行解耦.给出了详细的算法说明.     

Carathéodory系统解的存在性

将Carathéodory系统转化为Kurzweil广义常微分方程,利用已知的Kurzweil广义常微分方程解的存在性理论讨论了Carathéodory系统解的存在性.     

What can we learn from the fifties?

Economists have increasingly elicited probabilistic expectations from survey respondents. Subjective probabilistic expectations show great promise to improve the estimation of structural models of decision making under uncertainty. However, a robust finding in these surveys is an inappropriate heap of responses at “50%,” suggesting that some of these responses are uninformative. The way these 50s are treated in the subsequent analysis is of major importance. Taking the 50s at face value will bias any aggregate statistics. Conversely, deleting them is not appropriate if some of these answers do convey some information. Furthermore, the attention of researchers is so focused on this heap of 50s that they do not consider the possibility that other answers may be uninformative as well. This paper proposes to take a fresh look at these questions using a new method based on weak assumptions to identify the informativeness of an answer. Applying the method to probabilistic expectations of equity returns in three waves of the Survey of Economic Expectations in 1999–2001, I find that: (i) at least 65% of the 50s convey no information at all; (ii) it is the answer most often provided among the answers identified as uninformative; (iii) but even if the 50s are a major contributor to noise, they represent at best 70% of the identified uninformative answers. These findings have various implications for survey design.     

关于电子自旋不是一种经典模型

本文通过两种方法证明电子自旋不是一种经典模型。     

基于系统工程的系统分类法及应用

首先叙述了一般文献中对系统的分类，然后对钱学森为首的一批知名学者关于系统的人和了介绍。详细地讨论了Ｓｈｅｎｈａｒ和Ｂｏｎｅｎ对系统的二维分类法，并同钱学森的系统分类法进行联系，根据２－Ｄ分类法，提出了系统开发的三维结构，最后对其应用实例进行了说明。