检索结果-内蒙古大学图书馆

第27届中国过程控制会议（CPCC2016）

作者： HAN Hong-Gui GE Lu-Ming WU Li QIAO Jun-Fei College of Electronic Information and Control Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

This paper addresses the problem of designing a model for the sludge volume index(SVI).This model is realized by means of a multivariate local quadratic polynomial regression(MLQPR)method,in which,a quadratic polynomi... 详细信息

关键词： SVI A sludge volume index model based on the multivariate local quadratic polynomial regression method

来源：评论

学校读者我要写书评

暂无评论

A Heuristic Monte Carlo Tree Search Method for Surakarta Chess

A Heuristic Monte Carlo Tree Search Method for Surakarta Che...

引用

第28届中国控制与决策会议

作者： Guoyu Zuo Chenming Wu College of Electronic and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467397155

This paper proposes a heuristic Monte Carlo Tree Search(MCTS) method for a computer game,Surakarta *** proposed method uses heuristic knowledge to guide the search procedure heading to a better *** our implementation we use a CPU based root parallelization technology which permits many instances running *** reliability of our method has been proved to be considerably effective by experimental results.

关键词： Surakarta Monte Carlo Tree Parallelization

来源：评论

学校读者我要写书评

暂无评论

Corrigendum to “Mobile Robot Simultaneous Localization and Mapping Based on a Monocular Camera”

引用

Journal of Robotics 2017年第1期2017卷

作者： Songmin Jia Ke Wang Xiuzhi Li College of Electronic Information & Control Engineering Beijing University of Technology Beijing 100124 *** Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing 100124 ***

来源：评论

学校读者我要写书评

暂无评论

The cognitive development learning model and its application in autonomous navigation of mobile robot

引用

Revista de la Facultad de Ingenieria 2016年第3期31卷 111-127页

作者： Cai, Jianxian Ruan, Xiaogang Zhu, Xiaoqing School of Electronic and Control Engineering Beijing University of Technology No.100 Pingleyuan Chaoyang District Beijing100124 China Department of Disaster Prevention Instrument Institute of Disaster Prevention No.3 University Street Yanjiao Development District Sanhe Hebei065201 China Beijing Key Laboratory of Computational Intelligence and Intelligent System No.100 Pingleyuan Chaoyang District Beijing100124 China

In terms of the navigation problem of the mobile robot occurring in unknown environment, based on the cognitive and developmental mechanism of the biology, a cognitive development model for the autonomous learning navigation of the mobile robot is designed. Through autonomous insertion and deletion of neuron nodes in the neural network, the neural network with a dynamically adjusted structure is designed and the biological characteristics of living beings are imitated, thereby obtaining a network scale that matches the application requirements. The thermodynamic process is used to simulate the asymptotic properties of the animals. The cognitive learning algorithm is designed from the Monte Carlo method, the Metropolis algorithm and the annealing algorithm, and it is theoretically proved convergent. Based on the formation of the cognitive development process, the autonomous navigation activities of the mobile robot is under study. The experimental results show that, with the help of the cognitive development model, the robot automatically acquires knowledge and accumulates experience from the environment through cognition and development like animals. And the robot gradually forms, develops and improves the autonomous navigation skills in a self-organized way.

关键词： Robots

来源：评论

学校读者我要写书评

暂无评论

system development for micro-electrode assembly of cochlear implant

System development for micro-electrode assembly of cochlear ...

引用

IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Shaokui Weng Weibin Rong Zeyang Xia Hao Deng Yangzhou Gan Jing Xiong Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences Shenzhen China State Key Laboratory of Robotics and System Harbin Institute of Technology

ISBN: (纸本)9781467389600

Cochlear Implant is an implantable medical device for severe deafness patients to restore hearing function. The micro-electrode in cochlear implant is directly contacted with the human cochlea for signals transmission, thus its assembly is an important step of cochlear implant production. However, currently micro-electrode is assembled manually and the assembly precision and efficiency are unable to meet the industrial standard. In this paper, an automatic assembly system of micro-electrode for Cochlear Implant was designed. In this system, several mechanical mechanism specially for the micron level parts transmission and assembly were designed, including a wire feeder, a ring transmission mechanism, and a welding mechanism. And combined with the human-computer interaction interface, the effectiveness of the overall performance of the assembly system was verified by experiments.

关键词： Wires Welding Cochlear implants Assembly systems Tungsten Needles Electrodes

来源：评论

学校读者我要写书评

暂无评论

Multi-stage feature learning based object recognition and 3D pose estimation with kinect 6

Multi-stage feature learning based object recognition and 3D...

引用

6th International Conference on Information Science and Technology, ICIST 2016

作者： Zeng, Wei Liang, Guoyuan Guangdong, Can Wang Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Dept. Mechanical and Automation Engineering Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781509012206

Impressive achievements have been achieved over the years in object recognition and 3D pose estimation while detecting objects and estimating their 3D poses reliably is still a very challenging problem, especially for texture-less objects in heavily cluttered scenes. In this paper, we introduce an improved approach based on multi-stage feature learning to identify object as well as their 3D orientation efficiently. Our approach is motivated by visual neuroscience models. Currently similar architectures have been successfully applied to pedestrian detection, traffic recognition, face representation, etc. We compute the feature descriptors by multi-stage convolutional neural networks (CNNs) which could map the object identity and 3D poses to the Euclidean distance space by evaluating the similarity between descriptors. By contrast with classical approaches, our method relies on fast and approximate Nearest Neighbor (NN) matching to solve the large scale problems instead of one classifier per object or multi-class classifiers whose complexity grows rapidly with the number of objects. The experiments of detecting poorly-textured objects in cluttered scenarios have been carried out to verify the effectiveness and efficacy of the proposed approach. © 2016 IEEE.

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect

A canonical correlation analysis based EMG classification al...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Zhe Fan Zhong Wang Guanglin Li Ruomei Wang National Engineering Research Center of Digital Life Sun Yat-sen University Guangzhou China Key Laboratory of Human-Machine-Intelligence Synergic System Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781457702198

Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

关键词： Training Electrodes Correlation Electromyography Pattern recognition Prosthetics Feature extraction

来源：评论

学校读者我要写书评

暂无评论

An Abstract Communication Service Interface of DPWS on Embedded Device in Industrial Automation

An Abstract Communication Service Interface of DPWS on Embed...

引用

第28届中国控制与决策会议

作者： Dandan Xu Bin Fang Huijie Li College of Electronic and Control Engineering Beijing University of Technology Engineering Research Center of Digital Community Ministry of Education Beijing Laboratory for Urban Mass Transit Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467397155

In view of the aging society,intelligent devices are more and more widely used in the field of industrial *** future factory will be dominated by Service-oriented Architecture(SOA).Devices can be abstracted by web services to enable their flexibility,dynamicity and interoperability with other *** paper presents an abstract communication service interface for web services that contributes to providing the flexible,loosely coupled system on embedded devices in an automatic industrial production line in which the implementations of the interface is constructed by the Devices Profile for Web Services(DPWS).It shows promising results in the remote data transmission without human intervention between the embedded server and enterprise information system.

关键词： SOA DPWS resource-constrained device Factory Automation

来源：评论

学校读者我要写书评

暂无评论

Fault Detection of Chiller Based on Improved KPCA

Fault Detection of Chiller Based on Improved KPCA

引用

第28届中国控制与决策会议

作者： Nanhua Zhang Xuejin Gao Yafen Li Pu Wang College of Electronic and Control Engineering Beijing University of Technology Engineering Research Center of Digital Community Ministry of Education Beijing Laboratory for Urban Mass Transit Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467397155

Principal component analysis(PCA) is a common fault detection *** it is difficult to get high accuracy,if it is applied to complex nonlinear *** with complex system such as chiller,this paper proposes using kernel principal component analysis(KPCA) for fault ***,the selection of kernel parameters is a problem in the implement of KPCA *** algorithm(GA) is used to determine the kernel parameter through minimizing false alarm rate and maximizing detection *** method is verified by ASHRAE 1043-RP *** results show that it is better than *** it can improve the accuracy of fault detection.

关键词： chiller PCA GA KPCA fault detection

来源：评论

学校读者我要写书评

暂无评论

Research on Subway Passenger Flow Combination Prediction Model Based on RBF Neural Networks and LSSVM

Research on Subway Passenger Flow Combination Prediction Mod...

引用

第28届中国控制与决策会议

作者： Pu Wang Cuixia Wu Xuejin Gao College of Electronic and Control Engineering Beijing University of Technology Engineering Research Center of Digital Community Ministry of Education Beijing Laboratory for Urban Mass Transit Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467397155

In view of the subway passenger flow's random problem,nonlinear problem and so on,in order to predict the subway passenger volume more accurately,this paper designs a kind of parallel variable coefficient weighted combination prediction model based on Radial Basis Function Neural Network and Least Squares Support Vector *** this method,firstly,the original data is ***,this paper respectively sets up RBF Neural Network and LSSVM prediction model for training and calculating the weighting coefficient with the results of the *** this paper separately does two kinds of models' prediction,and weights to get *** article uses 2012 passenger flow data of Beijing DONGZHIMEN Station for experiments,which shows that the result of combination prediction model is more accurate than the result of single prediction model.

关键词： Subway passenger flow Combination prediction Variable coefficient RBF neural network LSSVM

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：