期刊文献+
共找到4篇文章
< 1 >
每页显示 20 50 100
An Algorithm for Cavity Reconstruction in Electrical Impedance Tomography
1
作者 FENG TIAN-HONG MA FU-MING 《Communications in Mathematical Research》 CSCD 2011年第3期279-288,共10页
We consider the inverse problem of finding cavities within some object from electrostatic measurements on the boundary. By a cavity we understand any object with a different electrical conductivity from the background... We consider the inverse problem of finding cavities within some object from electrostatic measurements on the boundary. By a cavity we understand any object with a different electrical conductivity from the background material of the body. We give an algorithm for solving this inverse problem based on the output nonlinear least-square formulation and the regularized Newton-type iteration. In particular, we present a number of numerical results to highlight the potential and the limitations of this method. 展开更多
关键词 electrical impedance tomography CONDUCTIVITY Levenberg-Marquardt (l-m algorithm
下载PDF
基于ease-off的通用加工参数的弧齿锥齿轮高阶反调修正研究 被引量:1
2
作者 占睿 阿达依·谢尔亚孜旦 丁撼 《机械设计与制造》 北大核心 2016年第9期205-209,共5页
利用高阶运动系数表示的通用加工参数用来进行弧齿锥齿轮的精确ease-off齿面反调修正。首先基于通用展成加工模型(UGM)采用高阶多项式函数表达的通用加工参数来定义真实高阶ease-off齿面。然后考虑到方程求解的强烈非线性引入敏感系数... 利用高阶运动系数表示的通用加工参数用来进行弧齿锥齿轮的精确ease-off齿面反调修正。首先基于通用展成加工模型(UGM)采用高阶多项式函数表达的通用加工参数来定义真实高阶ease-off齿面。然后考虑到方程求解的强烈非线性引入敏感系数矩阵和改进的带置信域策略的Levenberg-Marquardat(L-M)算法来获得精确稳定的通用加工参数反调量。最后基于通用加工参数的高阶反调方法被提出来主要包括:i)最优加工参数调整;ii)高阶ease-off齿面修正。 展开更多
关键词 通用加工参数 ease-off 弧齿锥齿轮 L—M算法 高阶反调修正
下载PDF
An improved potential field method for mobile robot navigation 被引量:1
3
作者 李广胜 Chou Wusheng 《High Technology Letters》 EI CAS 2016年第1期16-23,共8页
In order to overcome the inherent oscillation problem of potential field methods(PFMs) for autonomous mobile robots in the presence of obstacles and in narrow passages,an enhanced potential field method that integrate... In order to overcome the inherent oscillation problem of potential field methods(PFMs) for autonomous mobile robots in the presence of obstacles and in narrow passages,an enhanced potential field method that integrates Levenberg-Marquardt(L-M) algorithm and k-trajectory algorithm into the basic PFMs is proposed and simulated.At first,the mobile robot navigation function based on the basic PFMs is established by choosing Gaussian model.Then,the oscillation problem of the navigation function is investigated when a mobile robot nears obstacles and passes through a long and narrow passage,which can cause large computation cost and system instability.At last,the L-M algorithm is adopted to modify the search direction of the navigation function for alleviating the oscillation,while the k-trajectory algorithm is applied to further smooth trajectories.By a series of comparative experiments,the use of the L-M algorithm and k-trajectory algorithm can greatly improve the system performance with the advantages of reducing task completion time and achieving smooth trajectories. 展开更多
关键词 potential field OSCILLATION Gaussian model Levenberg-Marquardt (l-malgorithm k-trajectory
下载PDF
Structural form selection of the high-rise buildingwith the improved BP neural network
4
作者 Zhao Guangzhe Yang Hanting +2 位作者 Tu Bing Zhou Meiling Zhou Chengle 《High Technology Letters》 EI CAS 2020年第1期92-97,共6页
As civil engineering technology development,the structural form selection is more and more critical in design of high-rise buildings.However,structural form selection involves expertise knowledge and changes with the ... As civil engineering technology development,the structural form selection is more and more critical in design of high-rise buildings.However,structural form selection involves expertise knowledge and changes with the environment which makes the task arduous.An approach utilizing improved back propagation(BP)neural network optimized by the Levenberg-Marquardt(L-M)algorithm is proposed to extract the main controlling factors of structural form selection.Then,an intelligent expert system with artificial neural network is constructed to design high-rise buildings structure effectively.The experiment tests the model in 15 well-known architecture samples and get the prediction accuracy of 93.33%.The results show that the method is feasible and can help designers select the appropriate structural form. 展开更多
关键词 BACK propagation(BP)neural network HIGH-RISE building STRUCTURAL form selection Levenberg-Marquardt(l-m)algorithm
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部