机构

• 自动化研究所 [4]
• 长春光学精密机械与物... [3]
• 过程工程研究所 [1]
• 沈阳自动化研究所 [1]
• 西安光学精密机械研究... [1]

采集方式

• OAI收割 [10]

内容类型

• 会议论文 [4]
• 期刊论文 [4]
• 学位论文 [2]

发表日期

• 2022 [1]
• 2020 [1]
• 2014 [1]
• 2011 [3]
• 2010 [3]
• 2007 [1]
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浏览/检索结果: 共10条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Accurate Quantitative Analysis of Valuable Components in Zinc Leaching Residue Based on XRF and RBF Neural Network 期刊论文  OAI收割 SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 卷号: 42, 期号: 2, 页码: 490-497 作者:  Li Yuan;  Shi Yao;  Li Shao-yuan;  He Ming-xing;  Zhang Chen-mu   |  收藏  |  浏览/下载：40/0  |  提交时间：2022/06/15 XRF  Accurate quantitative analysis  RBF neural network model  Zinc smelting leaching slag   Neural-Adaptive Finite-Time Formation Tracking Control of Multiple Nonholonomic Agents with a Time-Varying Target 期刊论文  OAI收割 IEEE Access, 2020, 卷号: 8, 页码: 62943-62953 作者:  Zhou, Kai-Bo;  Wu, Xiao-Kang;  Ge, Ming-Feng;  Liang, Chang-Duo;  Hu, Bing-Liang   |  收藏  |  浏览/下载：28/0  |  提交时间：2020/05/19 Multiple nonholonomic agent system (MNAS)  leader-following formation tracking problem (FTP)  radial basis function (RBF) neural network  distributed controller-estimator algorithm(DCEA)   Robust adaptive neural network control for a class of uncertain nonlinear systems with actuator amplitude and rate saturations 期刊论文  OAI收割 NEUROCOMPUTING, 2014, 卷号: 125, 页码: 72-80 作者:  Yuan, Ruyi;  Tan, Xiangmin;  Fan, Guoliang;  Yi, Jianqiang 收藏  |  浏览/下载：42/0  |  提交时间：2015/08/12 Actuator saturation  RBF neural network  Adaptive control  Robust control   An Efficient Tree Classifier Ensemble-Based Approach for Pedestrian Detection 期刊论文  OAI收割 IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2011, 卷号: 41, 期号: 1, 页码: 107-117 作者:  Xu, Yanwu;  Cao, Xianbin;  Qiao, Hong 收藏  |  浏览/下载：23/0  |  提交时间：2015/08/12 Efficient classification  false-positive rate (FPR)  pedestrian detection  performance evaluation  radial basis function (RBF) neural network.   Study of experimental design and Response Surface method for surrogate model of computational simulation (EI CONFERENCE) 会议论文  OAI收割 2nd Annual Conference on Electrical and Control Engineering, ICECE 2011, September 16, 2011 - September 18, 2011, Yichang, China Xi R.; Jia H.; Xiao Q. 收藏  |  浏览/下载：21/0  |  提交时间：2013/03/25 While the high-precision simulation is widely used in science and technology  Design of Experiment (DOE) based on Response Surface (RS) method can be employed in surrogate model to reduce the cost and error. In order to illustrate the relationship between parameters and response features  several DOE methods and Response Surface (RS) method are studied. The author used polynomial regression and RBF neural network based on orthogonal array to build a rocket aerodynamic discipline surrogate model respectively which proved their feasibility. From the results of the test case  conclusion is drawn that characteristic as well as acclimatization of DOE methods and different approximation should be considered for different issues  so the factors of cost and accuracy could reach a balance synthetically. 2011 IEEE.   Neural Network Predictive R2R Control to CMP Process 会议论文  OAI收割 2011 4th IEEE International Conference on Computer Science and Information Technology, Chengdu, China, June 10-12, 2011 作者:  Wang L(王亮);  Hu JT(胡静涛) 收藏  |  浏览/下载：47/0  |  提交时间：2012/06/06 chemical mechanical polishing  RBF neural network  predictive control  run-to-run control  PSO rolling optimization   图像序列中的光流估计与运动分割 学位论文  OAI收割 工学硕士, 中国科学院自动化研究所: 中国科学院研究生院, 2010 马东民 收藏  |  浏览/下载：52/0  |  提交时间：2015/09/02 统计学习模型  马尔科夫随机场  RBF模型  约束函数选择  运动分割  图像序列  statistical modeling  markov random field  radial basis function neural network  motion selection  motion segmentation  image sequence   The costs prediction of AOD furnace based on improved RBF neural network (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 Na T.; Zhang D.-J.; Hui L. 收藏  |  浏览/下载：17/0  |  提交时间：2013/03/25 In order to predict the cost  a model of cost prediction was set up based on adaptive hierarchical genetic algorithm and RBF neural network. Hierarchical genetic algorithm could optimize the topology and the parameters simultaneously. Compared with simple genetic algorithm  it has more efficiency in not only accelerating and stabilizing the parameters training but also determining the structure of the network. Adaptive crossover and mutation probability could accelerate the speed and avoid prematurity. The model was tested by five samples. The results showed that the prediction model has high prediction accuracy  which indicated that it was applicable to predict the cost by the model. 2010 IEEE.   Prediction model of molten iron endpoint temperature in AOD furnace based on RBF neural network (EI CONFERENCE) 会议论文  OAI收割 2010 International Conference on Logistics Systems and Intelligent Management, ICLSIM 2010, January 9, 2010 - January 10, 2010, Harbin, China Ma H.-T.; You W.; Chen T. 收藏  |  浏览/下载：28/0  |  提交时间：2013/03/25 According to Jilin Ferroalloy Factory 10-ton AOD furnace actual smelting condition  analyzes the impact factor of AOD furnace molten iron endpoint temperature  by optimizing the neural network connection weights and structure  design prediction model of molten iron endpoint temperature based on RBF neural network  using LM algorithm and 50 furnaces actual production data to train the model  and predicts another 50 furnaces molten iron temperature  Result shows that prediction model of molten iron endpoint temperature based on RBF neural network has a high accuracy  when the error of endpoint temperature is 12 C  hit rate of temperature is 82.4%. 2010 IEEE.   输出PDF建模与控制及其在火焰温度场中的应用 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, 2007 作者:  孙绪彬 收藏  |  浏览/下载：47/0  |  提交时间：2015/09/02 锅炉温度场重建  输出概率密度函数控制  射流火焰  迭代学习控制  RBF网络  预测控制  广义系统  Boiler temperature restructure  output PDF control  jet flame  iterative learning control  RBF neural network  predictive control  singular systems