查询词典 algorithms

Because of their intrinsic characteristics of hard computability, they cannot be solved accurately by efficient algorithms up to now. Since these problems have many applications in real situations, it is quite important to find some applicable algorithms.

由于难计算是这类问题的固有性质，因此它们目前尚无法用有效算法精确求解，但这些问题在现实领域中有着许多广泛的应用，因而寻找其实际而有效的算法就显得颇为重要了。

Computational algorithms of BEM for both multi connected domain and composites with particle of arbitrary geometry are derived.These BEM algorithms are used to calculate the temperature distributions for composites with both single-particle model and multi-particles models.

首先推导了多连域和含任意形状夹杂复合材料温度场问题的边界元计算格式，随后采用边界元法计算了具有不同形状和界面性能的单夹杂和多夹杂模型内的温度场。

Data stream model is different from traditional database. It has the characteristics of rapidness, real-time, continuousness and boundlessness. Therefore, the algorithms for mining data streams have substantial difference from that of traditional database mining. They are one-pass algorithms.

数据流模型不同于传统的数据库模型，具有快速、实时、连续、无界等特点，由此决定了数据流的查询或挖掘算法与基于传统的数据库的挖掘技术有显著的区别，其算法应是单遍扫描的。

Secondly, after studying modeling nonlinear systems using Volterra series model, the adaptive algorithms are presented. It is also investigated that step factor controls the convergence of the algorithms.

其次，研究了基于Volterra级数模型的非线性系统的自适应辨识问题，提出了基于Volterra滤波器的自适应算法，讨论了步长因子的确定问题以及对算法收敛性的影响。

A new and efficient geometrical correction algorithm is proposed for MODIS IB data, and possesses of the merits of forward mapping and inverse mapping algorithms; 3. Algorithms to remove stripe noise in MODIS IB data are developed, including Fourier Transform, Wavelet Transform and interpolation method; 4. MODIS data composite algorithm is developed, and a 16-day composite map covering entire China and its outward is produced.

本文介绍了开发MODIS数据基础处理软件的基本算法和成果，主要包括：(1)用C++语言开发和实现了MODIS数据基础处理软件；(2)研究和发展了一个普适的、全新的、兼有前向映射和后向映射优点的MODIS 1B数据几何纠正算法；(3)研究和实现了MODIS条带噪声消除算法，包括傅立叶变换、小波变换和插值三种算法，并对其进行了比较；(4)研究和实现了MODIS影像合成算法，并在此基础上完成了中国及周围地区16天MODIS彩色影像和植被指数的合成。

For the limitations of the traditional algorithms that can not be reasonably used to predict the traffic, this paper adopted the BP neural network and curvilinear regression coupling algorithms to add the inadequate.

摘 要：针对传统交通量预测方法中的局限性，采用BP神经网络与曲线回归耦合算法，用BP神经网络对历史数据训练，利用曲线回归对各因素待测年份之值进行预测，将各因素的预测值带入已训练好的BP神经网络中，即可得到未来交通量的预测值。

For the limitations of traditional algorithms that can not be reasonably accurately predict the traffic, we have adopted BP neural network and curvilinear regression algorithms. First, we use BP neural network to train on historical data and then use the curve of regression to predict various factors, and then forecast data into the trained BP neural network which has been trained well, you can get future traffic forecasts.

针对以上传统算法的局限性，采用BP神经网络与曲线回归耦合算法，用BP神经网络对历史数据训练，利用曲线回归对各因素待测年份之值预测，将各因素的预测值带入已训练好的BP神经网络中，即可得到未来交通量的预测值。

Comparing with other deblocking algorithms related with shifted blocks, the algorithms in this dissertation constructed shifted blocks with different shifting position in each shifting.

与其他使用偏移块的块效应消除算法不同的是，PDCT-BAR算法的每一次偏移过程都构造了具有不同偏移位置的偏移块。

If you want to deepen their understanding of algorithms, there are dozens of important algorithms.

详细说明：如果要加深对算法的理解，这里有十个重要的算法实现。

Finally the terminal rule of Genetic Algorithms has been proposed and the implementation of random number maker has been presented. Developed a genetic algorithms based system identification technique. Using this technique globally optimized models for linear and nonlinear system can be identified without the need of a differentiable cost function or linearly separable parameters.

然后提出了一种基于遗传算法的模型降阶方法，可一致地应用到连续系统和离散系统的模型降阶；最后提出了一种基于遗传算法的多目标通用控制器设计方法，可以满足不同的控制策略，而不是某一种特定的控制策略，计算机仿真结果充分验证了方法的正确性和有效性。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。