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On the basis of the conversion relation of inverse matrix and adjoint matrix, by using 1/ω instead of |B'(xBx(subscript k|, a new Landweber iteration formula x(superscript δ subscript k+1)=x(superscript δ subscript k)-ωB'(x(superscript δ subscript k)Bx(superscript δ subscript kB'x(superscript δ kf(x(superscript δ subscript k)-y(superscript δ)is constructed for solving rank deficiency nonlinear least squares problem, with which the phenomenon that leads to ill-posed problem because the iteration matrix is rank-deficient and very ill-conditioned in numerical iterative process is avoided.

基于逆矩阵和矩阵伴随算子的换算关系，并用1/ω代替|B′(xBx(下标k|，构造出一个新的求解秩亏非线性最小二乘问题的Landweber迭代格式，x(上标δ下标 k+1)=x-ωB'(xBx(上标δ下标 k*B'x(上标δ下标 kf(x-y，从而避免了在迭代过程中由于迭代矩阵的秩亏和病态而产生的不适定现象。

The example of a numerical prediction model shows the basic method of developing adjoint assimilation system of numeric predict model.

而后以一个数值预报模式为例，说明了构造伴随模式同化系统的基本方法。

In this paper a genetic algorithm four-dimension data assimilation system was applied to the more complex MM5 model, we verify the performance of the genetic algorithm assimilation system, we take the a heavy rainfall process during 04-05, July, 2003 as the experimental research object, and carry out data assimilation experiment of actual observation data, compare the experimental results of the genetic algorithm assimilation system and MM5 adjoint model assimilation system with the experimental results without assimilation, the following is the result:genetic algorithm assimilation system is used not only in a barotropic primitive equation but also in the complex model, MM5, for example, in the ideal experiment the result of the genetic algorithm assimilation system is better than the MM5 adjoint model assimilation system, in the assimilation experiment of actual observation data, whichever assimilation system is used, the initial field of numerical prediction model is effectively improved and the prediction effect of physical field and rainfall are somewhat enhanced.

本文将遗传算法的四维同化系统运用到更复杂的MM5模式中，在理想实验中验证遗传算法同化系统的性能，并以2003年7月4日"南京暴雨"作为研究对象，进行了实际观测资料的同化，并将遗传算法同化系统和MM5伴随模式同化系统得到的结果跟未同化的结果进行了比较，结果如下：遗传算法同化系统不仅可以用在正压原始方程模式上，同样也可以用在MM5等复杂模式上，理想实验证明了遗传算法同化系统优于MM5伴随同化系统，在实际观测资料同化中，采用两种方法的同化系统都能有效地改善数值预报模式的初始场，能在一定程度上提高物理量场和降水量的预报效果。

The Statistical Linearization Adjoint Method is utilized in the numerical simulations of this paper.

本文的仿真采用了统计线性化共轭方法。

The model was solved by the Ritz method, and the orthogonal polynomials generated by the Gram-Schmidt process were employed as admissible function for both disk and blades. With this approach, the matrix derived from kinetic energies becomes diagonal and numerical manipulation can become easy and stable.

采用Gram-Schmidt方法生成正交多项式作为李兹容许函数进行模型的离散化，简化了所得到的频率方程求解过程，有利於求解过程的数值稳定性，并可方便地通过对方程系数性质的分析了解结构振动模态的性质。

How to better simulate the advection and distribution of water substance has an important significance for the improvement of the numerical weather prediction, especially for precipitation.

如何更好地模拟水物质的平流和分布，对于数值天气预报效果的改进，特别是对于更好地模拟降水过程，具有重要的意义。

Finally, a numerical experiment was presented to discuss the effect of advection and nonlinear bottom stress to the warm water diffusion.

最后，利用数值试验，文章探讨了非线性底摩擦及平流项对温排水扩散的影响。

We studied the effect of particle impacting-angle on development of aeolian ripple s using numerical simulation method.

采用数值模拟的方法研究了沙粒冲击角对风成沙纹形成过程及其形态特征的影响。

Remarkable progress has been made in numerical simulation of aeolian ripple over the last more than twenty years.

风成沙纹的数值模拟研究已取得了不少进展，但各家所采用的模拟方法及模拟结果存在不少差异。

In this paper, the problems mentioned above are studied by both wind tunnel experiment and numerical simulation to improve the knowledge about aeolian grain transport, and impel the development of this subject.

因此，本文通过风洞实验和数值模拟对以上问题加以深入研究，以深化对风成地表颗粒物输运规律的认识，推进学科的发展。

Recall that, in the Kolmogorov axiomatization, measurable sets are the sets which have a probability or, in other words, the sets corresponding to yes/no questions that have a probabilistic answer.

延期开工的Kolmogorov宣布要衡量所有套职能有限许多坐标限制在于衡量子寅。换句话说，如果是/否的问题回答f可看的价值观念在许多最有限坐标，然后它有一个概率的答案。

The experimental results showed that the algorithm can filter singular points and remain fixity of the target edge.

实验表明：基于模糊理论的图像智能滤波方法比常规图像滤波方法运算量小，它既能去除奇异点，又能保持图像中目标的边缘不变性，具有很好的滤波效果。