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	Design and analysis of radial supports for a large aperture prism 会议论文 OAI收割 Shanghai, China, 2021-10-28 作者: Wen, Wansha; Ruan, Ping; Lv, Tao \| 收藏 \| 浏览/下载：34/0 \| 提交时间：2022/03/18 large aperture prism radial support finite element analysis optical surface evaluation
	A New Hybrid Forecasting Approach Applied to Hydrological Data: A Case Study on Precipitation in Northwestern China 期刊论文 iSwitch采集 WATER, 2016, 卷号: 8, 期号: 9, 页码: 15 作者: 收藏 \| 浏览/下载：51/0 \| 提交时间：2019/10/09 ensemble empirical mode decomposition radial basis function neural networks support vector machine hybrid approach precipitation prediction
	Classification of hyperspectral image based on SVM optimized by a new particle swarm optimization (EI CONFERENCE) 会议论文 OAI收割 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2012, June 1, 2012 - June 3, 2012, Nanjing, China 作者: Gao X.; Yu P.; Yu P. 收藏 \| 浏览/下载：19/0 \| 提交时间：2013/03/25 Support Vector Machine (SVM) is used to classify hyperspectral remote sensing image in this paper. Radial Basis Function (RBF) which is most widely used is chosen as the kernel function of SVM. Selection of kernel function parameter is a pivotal factor which influences the performance of SVM. For this reason Particle Swarm Optimization (PSO) is provided to get a better result. In order to improve the optimization efficiency of kernel function parameter firstly larger steps of grid search method is used to find the appropriate rang of parameter. Since the PSO tends to be trapped into local optimal solutions a weight and mutation particle swam optimization algorithm was proposed in which the weight dynamically changes with a liner rule and the global best particle mutates per iteration to optimize the parameters of RBF-SVM. At last a 220-bands hyperspectral remote sensing image of AVIRIS is taken as an experiment which demonstrates that the method this paper proposed is an effective way to search the SVM parameters and is available in improving the performance of SVM classifiers. 2012 IEEE.
	Optimization analysis for radial support by finite elements method (EI CONFERENCE) 会议论文 OAI收割 2012 International Conference on Intelligent System and Applied Material, GSAM 2012, January 13, 2012 - January 15, 2012, Taiyuan, Shanxi, China 作者: Wang Y.; Wang Y.; Wang Y.; Li C.; Wang Y. 收藏 \| 浏览/下载：22/0 \| 提交时间：2013/03/25 Primary mirror' surface figure is affected by supporting structure obviously. Especially for large-aperture telescope the surface figure is significant because of primary mirror' self-weight. For the requirement of the usage it's necessary to minimize the surface figure from self-weight by reasonable supporting scheme. The text optimized support point and force of radial support to minimize the surface figure by finite-element software. At the same time it studied the relationship between support point and counterweight to reduce the weight of support structure. At last it gave the optimal solution. (2012) Trans Tech Publications.
	A modified support vector machine model for credit scoring 期刊论文 iSwitch采集 International journal of computational intelligence systems, 2010, 卷号: 3, 期号: 6, 页码: 797-804 作者: Liu, Xiaoyong; Fu, Hui; Lin, Weiwei 收藏 \| 浏览/下载：30/0 \| 提交时间：2019/05/10 Credit scoring Support vector machine Genetic algorithm Radial basis kernel
	The analysis of the large-diameter primary mirror deformation of surface figure in the temperature field (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China Feng S.-L. 收藏 \| 浏览/下载：19/0 \| 提交时间：2013/03/25 The effect on the deformation of the primary mirror surface figure of the temperature gradient has been discussed theoretically. And its effect under axis and radial temperature gradient is analyzed when optical axis and support ways of the mirror changed. It has been concluded that the effect on the surface figure of the axis gradient is larger than radial gradient and also found that the deformation is concerned not only with thermal and structural parameter but also directly with the magnitude and direction of the temperature gradient. 2010 IEEE.
	非线性自适应逆控制方法研究学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2006 作者: 柳晓菁收藏 \| 浏览/下载：113/0 \| 提交时间：2015/09/02 自适应逆径向基函数网络模糊神经网络支持向量机桥式吊车 adaptive inverse Radial based function networks Fuzzy neural networks Support vector machine Overhead crane