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- A Multi-Objective Genetic Algorithm for High Dimensionality Optimization Problem and Study of Its Convergence Properties 一种求解高维优化问题的多目标遗传算法及其收敛性分析
- The cable tray is made of aluminum metal alloy by extruding, high dimension precision, high intensity, artistic shape. 桥架采用铝合金型材挤压成型,尺寸精度高;强度好,外形美观;
- It can reduce classifier space with high dimension，and then learn a combiner in lower dimension. 该方法将高维分类器空间压缩至低维分类器空间，并在该空间内学习集成器。
- It is valid for high dimension dataset, and it can find outliers accurately and validly. 实验结果表明，该算法能够识别任意形状的聚类，对高维数据有效，能够很好的识别出孤立点。
- As for the undivided linear sample space, the kernel function is needed to map onto another high dimension linear space. 对于线性不可分的样本空间，需要寻找核函数，将线性不可分的样本集映射到另一个高维线性空间。
- For complex functions with high dimensions, general particle swarm optimization methods are slow speed on convergence and easy to be trapped in local optima. 对于高维复杂函数,一般粒子群优化算法收敛速度慢,易早熟收敛。
- For the hexagonal work parts with high dimension accuracy requirement in diagonal, the sharp or round edge at the corner produced with less waste punching arrangement will influence its dimension precision. 对角线尺寸有精度要求的六角工件，在采用少无废料排样冲裁加工时，在其角尖部位产生圆角或披锋（刺）影响其尺寸精度。
- The data space was mapped to high dimension feature space with Mercer kernel function, and fuzzy kernel learning vector quantization (FKLVQ) was done on the feature space to obtain the effective and stable clustering weight vectors. 该方法通过Mercer核,将数据空间映射到高维特征空间,并在此特征空间上进行FKLVQ学习获取数据空间有效且稳定的聚类权矢量,然后在特征空间和输出空间上仅针对各空间的数据样本和它们各自的聚类权矢量进行Sammon非线性核映射。
- The support vector machine is a new statistical learning method. It can solve small-sample, non-linear and high dimension problems by using structural risk minimization (SRM) instead of empirical risk minimization (ERM). 支持向量机则是一门新的统计模式分类方法,支持向量机用结构风险最小化原则代替了经验风险最小化原则,同传统的模式识别方法相比,支持向量机在小样本、非线性及高维模式识别问题中表现出许多特有的优势。
- With the aborative description of geometry and analytics,applying Cartan Method,gets the Euler equation of weakly harmonic maps from high dimension Riemann manifold to homogeneous space. 借助于几何上与分析上的精细刻画;利用卡坦方法;得到高维Riemann流形到齐次空间弱调和映射体现的具体Euler方程形式.
- Humanoid beings exist in higher dimensions. 有人特点的生命存在于更高维度内。
- Support Vector Machine(SVMs) is a novel machine learning method based on statistical learning theory(SLT).SVM is powerful for the problem with small sample,nonlinear and high dimension. 支持向量机是以统计学习理论为基础发展起来的新的通用学习方法,较好地解决了小样本、高维数、非线性等学习问题。
- This kind of TFD can tune its kernel ambiguity function shape by two dimensional optimization procedure according to the characteristics of the analyzed signal. 这种时频分布根据被分析信号不同特性,采用优化方法自适应对模糊函数进行整形,尽可能保留集中在原点的信号模糊函数的自分量,抑制远离原点的交叉分量。
- The example of tooling shape design using this algorithm shows that high dimension accuracies can be achieved for general revolving parts with arbitrary cross-section shapes after two iterations. 实际计算结果表明，该算法具有较快的迭代速度，对一般形状的回转体零件可以在2次迭代后获得较高的零件精度。
- SVM solves practical problems such as small samples, nonlinearity, over learning, high dimension and local minima, which exist in most of learning methods, and has high generalization. 它较好地解决了以往困扰很多学习方法的小样本、非线性、过学习、高维数、局部极小点等实际问题,具有很强的推广能力。
- If you spend one day in a higher dimension you would come back one year later. If we go lower, time is more dense. 如果你在一个较高维度停留一天,你会需要一年之后才返回。如果我们去低维度,时间会变得更加密集。
- This method can be employed to detect the outliers of datasets with the number of outliers being unknown.Appling it into the “small sample，high dimension” microarray datasets achieves a good result. 算法应用于“小样本，高维度”的基因微阵列数据集进行样本孤立点检测取得了很好效果，证明了此方法的有效性。
- However, the classified proteomic data isn’t gotten easily, because of high dimension and noise.So, to analyze the data preprocess of proteomics is a very important part in this thesis. 但是，质谱技术在分类工作中往往受到资料维度过高与杂讯干扰所困扰，所以蛋白质体分析的前置处理在本文中是很重要的一环。
- Soft sensor modeling of selectivity to acrylonitrile using kernel PLS and kernel PCR is proposed to cope with the nonlinearity and multi high dimension of input and collinearity problem of process. 提出了用核函数PLS与核函数PCR建立工业丙烯腈生产过程丙烯腈收率软测量模型,以便更有效地处理过程非线性、多输入和数据共线性等复杂特性。
- At last symplectic schemes of Hamiltonian system for nonlinear Schrodinger equation have been extended to higher dimension. 最后，把非线性Schr(?) dinger方程的辛格式推广到了高维，并给出了一种特殊的非线性Schr(?)
