由于标准免疫算法采用二进制编码，在高维数问题求解时精度不高，求解时间长。
The standard IA was encoded with binary, and the solution of the problem which in high dimension have a lower precision and the running time is very long.
模糊粗糙集理论是解决数据集维数问题的有效工具，但基于模糊粗糙集的降维算法还不多。
Fuzzy rough set theory is an effective tool for reduction of data dimension, but there are few dimension reduction algorithms that are based on fuzzy rough set theory so far.
基于粗糙集和神经网络的人脸识别方法是针对PC A方法中存在的高维数问题和它对未训练过的样本识别率低的缺点而提出的。
Face recognition based on rough set and neural network was proposed for the shortcoming of high dimension of PCA face recognition and low recognition rate for non-training samples.
同时针对神经网络易于陷入局部极值、结构难以确定和泛化能力较差的缺点，引入了能很好解决小样本、非线性和高维数问题的支持向量回归机来进行油气田开发指标的预测；
The method of support vector regression which can well resolve the problem with the insufficient swatch, nonlinear and high dimension is introduction to predict the development index of gas-field.
他补充道，“在这里，数据的维数和容量是个大问题，要依靠计算来找到我们想要找寻的模式会变得极为困难。”
We are now at the point where the dimensionality and size of the data is a big problem. It makes things computationally very difficult to find these patterns we want to find.
在这两个极端之间还有这样的问题，当维数改变时它们的解答不变，但（证明的）技巧则不然。
Between these two extremes there are the questions for which the answers are invariant under change of dimension, but the techniques are not.
本文给出了证明矩阵行空间维数等于列空间维数的另一种较简单的证法，以及解决几个相关问题的捷径。
This paper give an expositior of simple way to display that the dimension of row space of matrix equals to the dimension of column space and some shortcuts to solve the problems concerned.
因为特征抽取减少了问题的维数并且使网络能够在一幅和实验图像分离的图像上得到训练。
Feature extraction reduces the dimensionality of the problem and enables the neural network to be trained on an image which is separated from the test image.
随着数据集的数据量和维数的增加，建立高效的、适用于大型数据集的分类法已成为数据挖掘的一个挑战性问题。
With the growth of data in volume and dimensionality, it has become a very challenging problem to build a high-efficient classifier for large databases.
从而解决了文本处理中的同义词和一词多义问题，在很大程度上降低了特征空间的维数，并且得到了较优的性能。
Thus we solve the problems of the synonym and the multivocal word, and reduce the dimension of the characteristic space to a great extent, get the correct rate of more excellent classification.
支持向量机(SVM)作为一种新型的非线性建模方法，适合于处理小样本和高维数的建模问题。
Support vector machines (SVM) is a new nonlinear modeling method which is suitable for solving small samples and high dimension modeling problems.
在软测量建模过程中，基于支持向量机的算法能较好地解决小样本、非线性、高维数、局部极小点等问题。
In model establishment of soft-sensing, the problems of small sample, non-linearity, high dimensions and local minimal value can be well solved by support vector machine algorithm.
解决的主要问题是把模的平坦分解推广为FP-平坦分解，利用维数从另一个角度来描述FP-平坦模的一些重要性质。
The main problems solved are that the flat decompositions are generalized to FP-flat decompositions, and some important properties of FP-flat modulus are described through dimensions in another way.
作为一种新的机器学习方法，SV M能较好地解决小样本、非线性、高维数和局部极小点等实际问题。
As a new machine learning method, SVM can solve the small sample, nonlinear, high dimension and local minima, the actual problem.
这些方法，仅对地基-基础界面进行有限元离散，使问题的空间维数减少一维；
Only the subsoil-foundation boundary is discretized, the same as boundary element method, which reduces the spatial dimension by one.
主成分回归以其能够有效的降低维数，克服回归问题中的自变量高度相关而产生的分析困难，而得到广泛的利用。
PCR (principal component regress) that with the characters of reducing dimensions effectively and overcoming the intense relativity between independent variables, is widely used in different fields.
对于这样一个高维数、非线性的小样本问题，许多传统的模式识别方法都容易出现过学习或欠学习现象。
When solving this small sample problem with high dimension and nonlinear, many traditional pattern recognition methods will tend to occur overfitting phenomenon.
增广向量法通过扩充输入、状态、输出等向量的维数及系统系数矩阵维数构造增广系统，使复杂问题简单化。
An augmenting system is designed to extend dimension of input, state, output and the coefficient matrixes in the method of augmenting vectors in order to predigest complicated problem.
电源优化问题具有高维数、非线性、随机性等特点，常规的优化算法难以求解到最优解。
The generation expansion optimization is high dimension, nun-linear, randomness problems. The convention algorithm hardly finds the best solution.
传统的统计方法不能够有效的处理如此高维数的特征向量，但是支持向量机就能够解决这一问题。
Traditional statistical method cannot deal with feature vectors with so high dimensions efficiently, but SVM (Supported vector Machine) could resolve this problem.
它在解决小样本、非线性及高维数等问题中表现出许多特有的优势。
It has many particular advantages on resolving such problems as small sample, nonlinearity and high dimension.
本文提出了三绕组变压器的一种新的三相模型，这种模型避免了现有模型存在的误差大或维数高以及奇异性问题。
A kind of three-phase models of three-winding transformers were presented which overcame some drawbacks in the existent models such as the large error or high dimension and singularity.
按照维数及类别的不同，将各种评定问题归结为统一的规划模型。
The method of LSPP developed has a generalized model applicable to geometrical error problems for various dimensions and types.
使问题的维数，对各级渐近解而言，降低了一维。
For every order of the asymptotic solution, the dimensionality of the problem has been decreased by one.
确定投影空间维数和建立投影空间模型是计算机视觉领域中形态图计算时一个十分重要的基本问题。
The establishment of dimensions and models of viewing space is quite important for computing aspect graph in computer vision.
结果表明基于分解协调的人工鱼群算法收敛性好，提高了计算速率，较好的解决了作物优化配水大系统中常见的变量维数高、约束方程多等问题；
In the result, the artificial fish school algorithm based on decomposition and coordination method shows its advantages on computing speed, convergence and solving dimension difficulty.
数论网格法适用于几何形状规则和维数不太多的问题，它的误差是真正的误差。
Number theory grid method is suited to the problems of regular geo metric shapes and those of not too more dimensions. Its error is a true error.
MDP作为一个复杂的离散事件系统，尤其是对于存在“维数灾”和“模型灾”问题的系统，其管理与控制问题难以用一般的常规方法来解决。
As a complex DEDS, there usually exists especially the curse of dimensionality and the curse of model, the problems of MDP's management and control can not be solved by regular methods.
高维数据的本征维数估计问题研究，在高维数据处理领域中有着重要的地位。
The intrinsic dimension estimation of high-dimensional data, is important in the field of high-dimensional data processing.
高维数据的本征维数估计问题研究，在高维数据处理领域中有着重要的地位。
The intrinsic dimension estimation of high-dimensional data, is important in the field of high-dimensional data processing.
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