本文采用高斯变异遗传算法作优化技术，实现了KPCA和GA的集成，适合核函数参数的优化选择。
In the paper, GBGM-GA is seen the optimization technique combining KPCA and GA, and is suitable to the optimization selection of kernel function parameter.
核函数是SVM的关键技术，核函数的选择将影响着支持向量机的学习能力和泛化能力。
Kernel function is the key technology of SVM, the choice of kernel will affect the learning ability and generalization ability of SVM.
通过线性规划技术和采用尺度函数作为核函数来实现支持向量回归模型。
Using linear programming technique and scaling kernel function, the support vector regression model was obtained.
该系统提高识别率的技术关键是SVM核函数的选取及其参数优化。
The key technology improves the system recognition rate is the SVM kernel function and parameter optimization.
介绍了几种新的基于核函数方法的软测量建模技术，并提出了针对复杂工业过程的混合核函数软测量建模方法。
Several new modeling technologies based on kernel function are introduced and the modeling method of soft measurement based on hybrid kernel function is stated for complicated industrial processes.
本文在研究了众多边缘检测方法的基础上，重点研究了最小二乘支持向量机（LS-SVM）的图像边缘检测技术，提出了一种基于混合核函数最小二乘支持向量机的图像边缘检测方法。
On the basis of studying on least-squares support vector machines (LS-SVM) of the image edge detection technology, Proposed a new method, which is based on mixed Kernel LS-SVM image edge detection.
此外，基于核的技术关键在于核函数以及核参数的选取，核函数不同及核参数不同都会影响状态监测的效果。
Furthermore, the selection of kernel functions and parameters is the task of key importance in kernel-based technology, which has a significant impact on monitoring results.
目标函数的构建和蒙特卡罗方法卷积核的获取，是调强放疗计划系统中的关键技术。
This paper mainly concerns two critical issues of IMRT: the objective function and the convolution kernels based on Monte Carlo method.
目标函数的构建和蒙特卡罗方法卷积核的获取，是调强放疗计划系统中的关键技术。
This paper mainly concerns two critical issues of IMRT: the objective function and the convolution kernels based on Monte Carlo method.
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