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An improved transient algorithm is proposed to solve the distributed parameter model for heat exchangers.

针对目前求解换热器瞬态模型的算法收敛性不稳定的问题,提出了一种改进算法。

As to the problem of divergency of conventional power flow method,By using an augment eqution this method can get the exact limit of voltage stability and the whole PV curve without encountering the numerical difficulty of ill-conditioning.

针对常规潮流法在鞍结分岔点附近不收敛,该方法通过增加一维潮流方程,消除了功率极限点附近的雅可比矩阵奇异的现象,获取精确的电压稳定极限和整支PV 曲线。

We establish a differential equation system via Newton method, and prove that the solution of nonlinear complementarity problems is exact the equilibrium point of differential equation system.

应用了牛顿的方法建立了微分方程系统,证明了非线性互补问题的解是所构造微分方程系统的渐近稳定平衡点,并给出了算法,证明了算法具有二阶收敛速度。

In the process of tracking target, using dynamic programming algorithm,which has the advantage of global optimization and constringency stability,to split the test target,and using the Kalman filter to predict the object center to help tracking the contour of the target, in order to implement the right moving target detection and tracking.

在跟踪过程中,结合动态规划法全局最优、收敛稳定的优点,对待检测目标进行分割,并采用卡尔曼滤波器预测目标中心来辅助跟踪目标轮廓,以实施对运动目标的检测和跟踪。

We construct an explicit finite difference approximation for the equation by using the equivalence relation between Riemann-Liouville fractional derivative and Grünwald-Letnikovmake fractional derivative.

再利用Riemann-Liouville分数阶导数与Grtinwald-Letnikov分数阶导数之间的等价关系,构造一显式有限差分近似,这一离散格式可以解释为一个随机游走模型,并且收敛于稳定的概率分布。

In conventional measurement work, total station, level, convergence gauge and other instruments are usually used. This method has the shortcomings such as slow speed, serious disturbance with the construction, finite object pionts,unstable measure quality and so on.

对隧道变形量测的传统方法大多是基于全站仪,水准仪,收敛计等设备,此种方式有着速度慢,与施工干扰较大,量测点数有限,量测质量不稳定等缺点。

The experimental results indicate that the LMBP neural network has higher classification rate, more rapidly converge velocity by comparing with other improved BP algorithm and the Radial Basis Function neural network. Through the experiments of recognizing the sonar image polluted with Gaussian noise, it is proved that the LMBP neural network has good stability and better anti-noise performance.

通过与标准BP算法和几种常用改进型BP神经网络以及径向基函数网络比较,验证了用LMBP神经网络作为声纳图像识别系统中的分类器,能够提高图像的识别率,加快网络的收敛速度,通过对受不同程度高斯白噪声污染的声纳图象的识别,验证了其性能稳定,具有较好的抗噪声性能。

This thesis carries on research to a class of nonlinear Schrodinger Equation with wave operator of initial value periodic problem.

本文针对一维带波动算子的Schrodinger方程周期初值问题进行数值研究,对上述方程首先构造了守恒的半离散格式,然后将p次Hermite插值方法与有限差分方法相结合构造了差分正交样条配置格式,并证明这两个格式均为稳定和收敛的格式。

Moreover, in the case of the inverse calculation, it was shown that the stable and efficient convergences were obtained.

并且由例证可见,反算的算法收敛稳定,计算效率高。

Computer simulation shows that, compared with the iterative and the Jacobi methods, the QR method is more accurate and stable.

在经由模拟测试后发现,相较於迭带法、Jacobi 法,QR演算法具备较佳的误差分布及较稳定的收敛性。

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