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This paper gives the probabilistic interpretation for one system of the second order quasilinear parabolic partial differential equations combined with an algebra equation using fully coupled forward-backward stochastic differential equation.

本文利用完全耦合的正倒向随机微分方程，对一类耦合了一个代数方程的二阶拟线性抛物型偏微分方程系统，给出概率表示。

Traffic momentum differential equation and Euler′s equation are constructed by means of differential calculus.

通过对交通流参数的微分分析，建立了交通流的运动微分方程和欧拉方程。

Because the equation is a various coefficients second-order parabolical partial differential equation,explicit difference formats usually have high condition for stability. Implicit difference formats have good stability,but they must calculate a set of algebraic equations,which are too complex.

由于泥沙扩散方程是一个二维变系数的抛物型方程，对于多维的方程，显格式往往稳定性要求很高，而隐格式虽然稳定性较好，但它要解大型的代数方程组，工作量也非常大，为了克服这两种格式的不足，常用ADI法求解，但仍存在一些计算量偏大等不足之处，因此构造出更好的差分格式是有必要的。

Among used machine learning methods, the gradient descent method is widely used to train various classifiers, such as Back-propagation neural network and linear text classifier. However, the gradient descent method is easily trapped into a local minimum and slowly converges. Thus, this study presents a gradient forecasting search method based on prediction methods to enhance the performance of the gradient descent method in order to develop a more efficient and precise machine learning method for Web mining.However, a prediction method with few sample data items and precise forecasting ability is a key issue to the gradient forecasting search method. Applying statistic-based prediction methods to implement GFSM is unsuitable because they require a large number of data items to model a prediction model. In the contrast with statistic-based prediction methods, GM(1,1) grey prediction model does not need a large number of data items to build a prediction model, and it has low computational load. However, the original GM(1,1) grey prediction model uses a mathematical hypothesis and approximation to transform a continuous differential equation into a discrete difference equation in order to model a forecasting model.

其中梯度法是一个最常被使用来实现机器学习的方法之一，然而梯度法具有学习速度慢以及容易陷入局部最佳解的缺点，因此，本研究提出一个梯度预测搜寻法则(gradient forecasting search method， GFSM)来改善传统梯度法的缺点，用来提升一些以梯度学习法则为基础的分类器在资讯探勘上的效率与正确性；而一个所需资料量少、计算复杂度低且精确的预测模型是梯度预测搜寻法能否有效进行最佳解搜寻之关键因素，传统统计为基础之预测方法的缺点是需要较大量的数据进行预测，因此计算复杂度高，灰色预测模型具有建模资料少且计算复杂度低等优点，然而灰色预测理论以连续之微分方程式为基础，并且透过一些数学上的假设与近似，将连续之微分方程式转换成离散之差分方程式来对离散型资料进行建模及预测，这样的作法不尽合理，且缺乏数学理论上的完备性，因为在转换过程中已经造成建模上的误差，且建模过程仅考虑相邻的两个资料点关系，无法正确反应数列未来的变化趋势。

This paper proposes a new differential equation for production declining rate ,which has different form from differential equation of J.

研究提出了一种新的产量递减率微分方程，这个方程与J J阿尔普斯的递减率微分方程在形式上是不同的，并由此推导出了一种油气藏可采储量预测方法。

In this paper, we extend the A-harmonic e equation from the constant differential form which values in zero to any differential form, that is p-harmonic type equation.

在本文中，我们主要是把A-调和方程从取特殊值0的常微分形式推广到任意给定的微分形式，即p-调和类型方程。

With the increasing development of science and technology, There are many problems relating to differential equation derived form lots of practi- cal applications, such as whether differential equation has a oscillating solution or not, and whether all of its solutions are oscillatory or not.

随着自然科学和生产技术的不断发展，在许多应用问题中均出现了微分方程是否有振动解存在或者微分方程的一切解是否均为振动解的问题。

The proposed method is sample and does not need to compute both complex partial differential equation and operator equation of Riccati.

该方法计算简单，无须计算复杂的偏微分Riccati方程或算子Riccati方程。

The boundary value problem for first-order differential equations with a parameter refers to the finite solution condition of equation which includes unknown quantity and its first-order derivative that not only relies on interval value but also relies on the parameter of the equation,which is always settled by fixed point theory or successive approximation method.

含一个参数的一阶微分方程边值问题是指：含有未知量及它的一阶导数的方程的定解条件不仅依赖于在区间端点的取值，而且依赖于方程中的参数。通常它用不动点定理或逐步逼近法来解决。

Reduce the computing complexity of magnetic field integral equation with differential quotient, which makes the computing which combined field integral equation more efficiently.

在AIM算法的实现技术方面作了两个改进：一是采用了新的多极子展开方案，保证了迭代的数值稳定性；二是在差商逼近偏导数的过程中全部采用二阶形式，保证了差商逼近偏导数的精度。

We stopped by the old fashion ice cream parlor Manhattan Beach Creamery for some refreshment. The "No Shoes, No Shirt, No Problem" sign on the wall epitomizes the beach lifestyle.

我们去商店区的一家老式冰淇淋店坐坐，墙上挂著「没鞋，没上衣，没问题」的牌子完全捕捉了海滩生活的随性及风格。

"If therefore", argues Bellarmine we can offer our prayers and our satisfactions in behalf of those detained in purgatory, because we are members of the great body of Christ, why may not the Vicar of Christ apply to the same souls the superabundant satisfaction of Christ and his saints--of which he is the dispenser?

" "因此，如果"，认为贝拉明（德indulgentiis ，十四）"我们可以提供我们的祈祷和我们满意的代表那些被拘留在炼狱，因为我们是成员的伟大基督的奥体，为什麼可能不是牧师基督适用於同样的灵魂满意的过剩是耶稣和他的圣人-他是在配药？