常在误差

词组短语

constant error

与常在误差相关的网络例句 [注：此内容来源于网络，仅供参考]

Then the FLUENT software was used to simulate the amphibious vehicle' ambient flow field through defining the unsteady boundary condition. The lift, resistance, velocity, pressure, and wave of the amphibious vehicle moving in the regular waves were obtained, which can avoid the errors resulted from neglecting the free surface and provides theoretic basis for the research on optimization design of high performance amphibious vehicle.

在计算出某改进型两栖车在微幅规则波中高速迎浪运动时升沉和纵摇特性的基础上，运用FLUENT软件，通过自定义非定常入口边界实现了两栖车在微幅规则波中运动的三维流场数值模拟，得到了升力、阻力、速度、压强和兴波等流场参数，实现了两栖车在波浪中的绕流场数值模拟，解决了以往由于忽略兴波特性导致数值计算结果随航速提高误差不断增大的问题，为高性能两栖车的外形设计研究提供了理论依据。

In Chapter 2, starting from the basic fractional ordinary differential equations,weapply a high order approximation of fractional derivative advanced by Lubich to frac-tional differential equation, construct a high numerical difference scheme to solve thefractional differential equation, present error analysis of the algorithms theoretically,and prove the consistency ,convergency and stability.

接下来的第二章中，首先从基本的分数阶常微分方程出发，对Lubich提出的一个关于分数阶导数的高阶近似，将其应用于分数阶微分方程，构造高阶数值差分格式来进行分数阶微分方程的数值求解，并在理论上给出这一算法的误差分析，证明了它的相容性，收敛性和稳定性。

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。

Also the problems of stochastic controllability, observability and stability of the filter are studied, a simple observability criterion for the time-invariant systems is set up, error band of the filtering is given theoretically, and the filtering stability results are proved under more general conditions; besides, the filtering error caused by uncorrect mathematical models is analysed.

本文还研究了随机能控能观性及滤波的稳定性问题，建立了结构简单的平稳定常系统的能观性判据，在理论上给出了滤波算法的误差范围，在更一般的条件下证明了最优滤波算法的稳定性；并从理论上分析了模型误差对滤波产生的影响。

In Chapter 4, we consider more complex fractional nonlinear differential equation,also using the high order approximation presented by Lubich to construct correspond-ing numerical scheme and giving the error analysis of the algorithms.

在第四章中，进一步的考虑更复杂的非线性分数阶常微分方程，同样利用的是Lubich提出分数阶导数的高阶近似，构造相应的数值格式，并给出这一算法的误差分析，即相容性，收敛性和稳定性的证明。

Methods and results We assume the carotid arterial wall is the elastic material so we can use the Hooke's law to analyze it. The experiment is based on the use of ultrasound B-mode imaging technique and the off-line image analysis. Elastic tube phantom experiments demonstrated the validity of the technique, providing the size of the tube within 3% of the actual values. The system was also tested in the common carotid arteries of 10 healthy males (age 23.6 y). According to the experimental result, it shows that our index is less variant than Peterson's elastic modulus. The results of and are and respectively.

根据橡皮管的体外实验结果，利用超音波以及影像分析所得到的橡皮管尺寸，与实际尺寸间的误差只有3%，而使用超音波 B-mode 量测颈动脉的实验结果显示，在把颈动脉当作完全弹性体的假设下，所得到的 CIMT 硬度指标，於十位平均年龄为23.6岁的年轻健康男性中，结果与过去文献中常使用的 Peterson's elastic modulus 相比较，结果显示容易受到不同受试者间，不同的生理状态之影响，而在考虑受试者的 IMT 变化情况下，比能够反映更多的受试者颈动脉材料性质，因此得到了较为稳定的实验结果。

But in the numerical calculation process, such as numerical differentiation, if we use these numerical methods inadequately, then it may be induced non necessary numerical error, including round off and truncation error.

因而常必须以值方法替代解析解，但是在值计算的过程中，很容引入额外的计算误差，包括舍位误差与截断误差。

In this paper,based on an improved orthogonal expansion in an clement , using the new idea of Ref.[3] ,a new error expression of n-degree Hermite finite element approximation to one-dimensional 4-degrec 2-point bounded problem and 2-degree ordinary differential problem, and then optimal order superconvergence for their first derivatives is obtained.

本文针对在改进的单元正交性估计的基础上，利用文[3]提出的新想法，得到一维四阶两点边值问题和二阶常微初值问题的n次赫米特有限元u_h∈C~1的新误差估计式，以及导数误差的最佳阶超收敛，并且两者有相同的超收敛结果。

The RANS governing equation and RNG κ-ε turbulence model were used, and the flow fields at different relative positions between blade and volute tongue in a centrifugal pump were simulated by using finite volume method, under the hypothesis of steady flow.

本文选择RANS方程和RNGk-ε湍流模型，采用有限体积法，在假定流动定常的前提下对离心泵中叶片与蜗舌不同相对位置时的流场进行数值模拟，总结分析了各性能参数的计算误差在不同的相对位置时的变化规律。

Without measuring the relative angles between objects, the validity of traffic accident on-site sketch is often challenged. In Taiwan, two common measuring methods for drawing a traffic accident on-site sketch: one is trilateration method, and another one is offset method. Both methods have their limits.

现行，常用於绘制交通事故现场图的量测方法有二：一为三定点法，此法常因测线间夹角过大或过小时，使得当测线彼此间的夹角有微小误差时，即造成颇大的位置偏移误差；另一方法为直角坐标法，此法应用在交通事故现场绘制的测量，假设目测标定於基准线与基准线外之测量点的连线成直角，若不为直角时，易造成绘制结果的偏差。

与常在误差相关的网络解释 [注：此内容来源于网络，仅供参考]

LO：本振

对于像LTE和WiMAX当中的正交频分复用(OFDM)信号,本振(LO)的相位噪声叠加在n个副载波上的. 这里的相位噪声有两个效果:(1)所有副载波的随机相位旋转常称为公共相位误差(CPE);(2)载频间干扰(ICI)是由给定的副载波被n-1个相邻的带有噪声的副载波恶化而产生的.