奇性常微分方程差分解的外推

本文利用 Crank—Nicholson 格式导出奇性微分方程,形如t∈[0,1],0<β<1,F(t)∈C~∞[0,1],F(0)≠0的差分解展开式,并对其展开式应用 Richardson 外推,使外推后的近似解(f)与真解 U(t)的误差在\{0}上达到 O(π~(2+β)).     

EXTRAPOLATION FOR FINITE ELEMENT METHODS OF THE FIRST KIND FREDHOLM INTEGRAL EQUATIONS

In this paper,a numerical analysis of finite element methods for Fredholm equationsof the first kind,which is based upon regularization,is made.It shows that extrapolationalgorithms can accelerate the convergence of approximate solutions.     

利用神经网络外推预测油田综合含水率

逻辑斯特（Ｌｏｇｉｓｔｉｃ）模型常被用来预测油田晚期勘探阶段的石油资源，还可用来预测一个油区的含水率变化过程。文中应用改进的神经网络算法和结构，预测油田的含水率变化趋势；并与Ｌｏｇｉｓｔｉｃ模型预测结果进行了比较，结果表明；神经网络是一种可行的石油资源外推预测方法。     

一般高维解析函数的外推

给出了一般高维解析函数的外推方法及外推的误差估计公式．     

无人作战飞机数据链延时对攻击决策的影响及其补偿

数据链是无人作战飞机与地面控制系统之间的纽带,但是数据链延时会使地面操作员对战场态势的判断存在滞后和误差,从而易引起决策不当。在分析了无人作战飞机对地攻击过程中数据链延时对攻击决策影响的基础上,采用Unscented卡尔曼滤波器估计了无人机和机动目标状态,然后采用一种状态外推算法和马尔科夫加速度模型分别对二者的状态进行了预测。仿真结果表明,该方法对数据链延时具有较好的补偿作用,可以减少因数据链延时造成的不良影响。     

Generative models: Human embryonic stem cells and multiple modeling relations

Model organisms are at once scientific models and concrete living things. It is widely assumed by philosophers of science that (1) model organisms function much like other kinds of models, and (2) that insofar as their scientific role is distinctive, it is in virtue of representing a wide range of biological species and providing a basis for generalizations about those targets. This paper uses the case of human embryonic stem cells (hESC) to challenge both assumptions. I first argue that hESC can be considered model organisms, analogous to classic examples such as Escherichia coli and Drosophila melanogaster. I then discuss four contrasts between the epistemic role of hESC in practice, and the assumptions about model organisms noted above. These contrasts motivate an alternative view of model organisms as a network of systems related constructively and developmentally to one another. I conclude by relating this result to other accounts of model organisms in recent philosophy of science.     

外推法消除实验系统误差的研究

对于某些实验，可用图像外推法消除系统误差。     

高维解析信号的外推

给出了高维解析信号外推的一种方法．并证明了这种方法的合理性．     

有限元法的高精度分析——超收敛性及后处理

对二阶方程的有限元法,我们综合了各种高精度算法,即超收敛点,局部平均法,外推及校正等,最后,为得到曲边区域上的整体结果,我们提出了在此区域上连续,且六片光滑的变换。