检索结果-内蒙古大学图书馆

Chinese Automation Congress

作者： Haijun Fu Ming Qiu Xisong Dong Gang Xiong Haonan Xiong Xiang Su Shichao Chen Zhen Shen Xiujiang Guo School of Artificial Intelligence Beijing Union University Beijing China The Cloud Computing Center Chinese Academy of Sciences Dongguan China The Qingdao Academy of Intelligent Industries Macau University of Science and Technology Qingdao China Beijing Union University Beijing China School of Electrical Engineering and Electronic Information Xihua University Chengdu China The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China Department of Computer Science University of Helsinki Fin Finland Measurement Center Station PetroChina Huabei Oilfield Company Renqiu China

There exist some obstacles to realize high-precision positioning with using the position differential technique due to the limiting factors. However, with the advancement of chip performance and the establishment of multiple satellite navigation systems, position differential positioning can be realized to meet the civilian high-precision positioning demand while significantly reducing costs. This paper is to explore the engineering application and propose a new method. Through the experiments and data analysis, we have found the error correlation between two receivers in a small area and designed a set of positioning system, and programmed in the Keil μVision5 in C language. The system consists of the current mainstream low-cost STM32, UBLOX NEO 6M chip, NRF24L01 chip, GPS antenna and power supply module. Each two receivers can form a differential positioning system. At present, the system in the low-speed status is, in the urban environment, basically reaching within 0.5 - 3 m of the positioning error.

关键词： Position differential positioning Low cost Error correlation GPS STM32

来源：评论

学校读者我要写书评

暂无评论

Multi-objective Design of the Water Distribution systems Using SPEA2 35

Multi-objective Design of the Water Distribution Systems Usi...

引用

第35届中国控制会议

作者： MENG Qinchao QIAO Junfei YANG Cuili College of Electronic Information and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

As a complicated and combinatorial optimization problem, the design of Water distribution systems(WDSs) is difficult to be solved. In this paper, in order to design WDSs better, three objectives are considered, including the initial construction cost, the sum of node surplus head and the variance of node surplus head. The consideration of the variance of node surplus head can reflect the distribution of the node surplus head in WDSs. This problem is solved by the strength pareto evolutionary algorithm(SPEA2). Finally, the model is applied into two well-known benchmark case studies, the two-loop network and the New York Tunnels network. By comparing with some algorithms, such as Tabu search algorithm and non-dominated sorting genetiv algorithm(NSGA2), the performance of SPEA2 shows the effectiveness in terms of reliability, convergence, as well as diversity.

关键词： Multi-objective optimization Water distribution systems SPEA2

来源：评论

学校读者我要写书评

暂无评论

A GPRFNN-based Control system for Wastewater Treatment Process 35

A GPRFNN-based Control System for Wastewater Treatment Proce...

引用

第35届中国控制会议

作者： HAN Gaitang HAN Honggui QIAO Junfei College of Electronic Information & Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

As a nonlinear and time-varying complex dynamic system, wastewater treatment process(WWTP) is difficult to be controlled. In this paper, to control the dissolved oxygen(DO) concentration in a WWTP, a growing and pruning recurrent fuzzy neural network(GPRFNN)-based control system is proposed which contains RFNN controllers and RFNN identifier. The identifier is used to model the WWTP with an adaptive algorithm to afford model information for the controllers, while the controllers are designed to adjust the control variables to make the WWTP run smoothly. Furthermore, the structure of the RFNN is self-organized to keep the output steady in structural adjustment phase, which is also theoretically proved. Finally, the control performance of the proposed system is shown by simulation results.

关键词： Wastewater Treatment Process Recurrent Fuzzy Neural Networks Dissolved Oxygen Self-organizing Mechanism

来源：评论

学校读者我要写书评

暂无评论

Prediction of PM2.5 based on Elman neural network with chaos theory 35

Prediction of PM2.5 based on Elman neural network with chaos...

引用

第35届中国控制会议

作者： HU Zhiqiang LI Wenjing QIAO Junfei College of Electronic Information and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781509009107

PM2.5 is difficult to accurately forecast due to the influence of multiple meteorological and pollutant variables in the complex nonlinear dynamic atmosphere *** this paper,an Elman neural network prediction method based on chaos theory is put forward for the ***,the chaotic characteristics of the concentration of the PM2.5 are analyzed and verified from the correlation dimension,the maximum Lyapunov exponent and the Kolmogorov ***,phase space reconstruction technique of chaotic theory is adopted to reconstruct the phase space of PM2.5 time *** reconstructed phase space and the future concentration of PM2.5 are taken as the input and output of the Elman neural network with chaos theory(Elman-chaos) *** numerical and experimental analyses show that this method is proportionally superior to that without considering the chaos characteristics and other *** Elman-chaos prediction model has better prediction performance and application value.

关键词： PM2.5 Chaos Phase space reconstruction Elman neural network Prediction

来源：评论

学校读者我要写书评

暂无评论

An Improved RANSAC Algorithm for Simultaneous Localization and Mapping

引用

Journal of Physics: Conference Series 2018年第1期1069卷

作者： Songmin Jia Zeling Zheng Guoliang Zhang Jinhui Fan Xiuzhi Li Xiangyin Zhang Mingai Li Faculty of Information Technology Beijing University of Technology Beijing China. Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China. Engineering Research Center of Digital Community Ministry of Education Beijing China.

Image feature matching is an important part of SLAM (Simultaneous Localization and Mapping algorithm). In order to improve the implementation efficiency of standard RANSAC algorithm, this paper proposed a novel improved RANSAC algorithm to deal with the mismatch in the image matching procedure. Our method deals with raw sample data and predict the inliers in the sample data according to the Euclidean distance between feature descriptors. And then we estimated the homography matrix with the selected sample. The homography matrix is used to eliminate the characteristics of mismatch. Furthermore, a binary environment dictionary is created for loop detection and the experimental results demonstrate that this method improves the speed of loading time of the dictionary and the accuracy of SLAM.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Structure design for RBF neural network based on improved K-means algorithm 28

Structure design for RBF neural network based on improved K-...

引用

28th Chinese Control and Decision Conference, CCDC 2016

作者： Yuqing, Sun Junfei, Qiao Honggui, Han College of Electronic Information and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9781467397148

Aiming at the disadvantages of the traditional K-means clustering algorithm, a new algorithm based on density is proposed to remove the noises and outliers in this paper. This algorithm determines whether a point is a noise or not according to the density of the point. Experiments show that this algorithm can effectively eliminate the influence of the noises when the K-means algorithm searches cluster centers in the samples. Then the subtractive clustering algorithm is used to initialize the clustering centers of the K-means algorithm, meanwhile the number of cluster centers is gotten. The improved K-means algorithm is taken to optimize the structure of RBF neural network, and the results of experiments on the typical function approximation show that the proposed algorithm has the better approximation ability. © 2016 IEEE.

关键词： Density K-means algorithm RBF neural network Subtractive clustering algorithm

来源：评论

学校读者我要写书评

暂无评论

Driver fatigue detection system based on DSP platform 22nd

Driver fatigue detection system based on DSP platform

引用

22nd International Conference on MultiMedia Modeling, MMM 2016

作者： Li, Zibo Zhang, Fan Sun, Guangmin Zhao, Dequn Zheng, Kun Department of Electronic Engineering Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing100124 China

ISBN: (纸本)9783319276731

Due to non-invasiveness, monitoring driver state in computer vision (CV) has become a major way to detect driver fatigue. In contrast to other researches, we brought the driver fatigue detection system on the basis of DSP platform, which can make contribution to application on the integrated system for vehicle. However, the conventional system cannot easily be transplanted into DSP due to its storage and computation capacity. Therefore, designing an algorithm that can detect the fatigue efficiently is goal in this study. As the most important part of system, the geometric relationship and shape information within near frontal face is employed in the eye detection part, which depicts the eyebrow, eye and nose. In experiment part, a self-made database is assembled to test the performance of system. As the results of experiment, the detection rate of eye is achieved at 92.71% and driver fatigue state is obtained at 97.5%. © Springer International Publishing Switzerland 2016.

关键词： Digital signal processing

来源：评论

学校读者我要写书评

暂无评论

Self-alignment for strapdown INS using real-time adaptive filter 7

Self-alignment for strapdown INS using real-time adaptive fi...

引用

7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016

作者： Jian, Zhao Fu-Jun, Pei Hong-Yun, Liu Beijing Key Laboratory of Computational Intelligence and Intelligent System School of Electronic Information and Control Engineering Beijing University of Technology 100124 China

ISBN: (纸本)9781467383189

As it is difficult to get an accurate mathematical noise model under various dynamic interference conditions, Strap-down Inertial Navigation system (SINS) was difficult to realize self-alignment. Although the fuzzy adaptive Kalman filter can be used to realize the SINS self-alignment, the algorithm complexity is high and the error term is unstable. To solve this problem, a novel self-alignment method using real-time adaptive filter was developed in this paper. This method is based on the theory of fuzzy adaptive adjustment and used the filter stability as the criterion. The exponential function was used to replace the fuzzy inference calculation, which eliminated the complex process of fuzzy, fuzzy inference and de-fuzzy. The stability and accuracy of the adaptive filter was also improved. Finally, the simulation process was used to test the algorithm of this method, and the results demonstrated that the self-alignment using real-time adaptive filter method reduced the complexity of the algorithm and had better stability and alignment accuracy. © 2016 IEEE.

关键词： Adaptive filters

来源：评论

学校读者我要写书评

暂无评论

Structure Design for RBF Neural Network Based on Improved K-means Algorithm

Structure Design for RBF Neural Network Based on Improved K-...

引用

第28届中国控制与决策会议

作者： Sun Yuqing Qiao Junfei Han Honggui College of Electronic Information & Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467397155

Aiming at the disadvantages of the traditional K-means clustering algorithm,a new algorithm based on density is proposed to remove the noises and outliers in this *** algorithm determines whether a point is a noise or not according to the density of the *** show that this algorithm can effectively eliminate the influence of the noises when the K-means algorithm searches cluster centers in the *** the subtractive clustering algorithm is used to initialize the clustering centers of the K-means algorithm,meanwhile the number of cluster centers is *** improved K-means algorithm is taken to optimize the structure of RBF neural network,and the results of experiments on the typical function approximation show that the proposed algorithm has the better approximation ability.

关键词： K-means algorithm Density Subtractive clustering algorithm RBF neural network

来源：评论

学校读者我要写书评

暂无评论

Step Light Application in Optical Tomography 35

Step Light Application in Optical Tomography

引用

第35届中国控制会议

作者： CHEN Zhilei FANG Bin LI Huijie WANG Pu 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)9781509009107

关键词： Step light Characteristic value Image reconstruction Forward model Response

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：