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International Conference on Intelligent Transportation

作者： Mingxia Sun Kunfeng Wang Ming Tang Fei-Yue Wang Jinfeng Yang Tianjin Key Laboratory of Advanced Signal Processing Civil Aviation University of China Tianjin China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences (CAS) Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences (CAS) Beijing China

This paper presents a generic video vehicle detection approach through multiple background-based features and statistical learning. The main idea is to configure several virtual loops (as detection zones) on the image, assuming moving vehicles may cause pixel intensities and local texture to change, and then by identifying such pixel changes to detect vehicles. In this research, multiple pattern classifiers including LDA + Adaboost, SVM, and Random Forests are used to detect vehicles that are passing through virtual loops. We extract fourteen pattern features (related to foreground area, texture change, and luminance and contrast in the local virtual loop zone and the global image) to train pattern classifiers and then detect vehicles. As experimental results illustrate, the proposed approach is quite robust to detect vehicles under complex dynamic environments, and thus is able to improve the accuracy of traffic data collection in all weather for long term.

关键词： Vehicles Feature extraction Training Image edge detection Vehicle detection Meteorology Radio frequency

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The strategies of avoiding energy holes in wireless sensor networks

The strategies of avoiding energy holes in wireless sensor n...

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2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

作者： Xu QIAN Zhengjie WANG Xiaoguang ZHAO School of Mechanical Electronic & Info. Engineering China University of Mining & Technology (Beijing State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automati

Wireless sensor networks are characterized by multihop network. Some nodes in network are required to forward a disproportionately high amount of traffic and die early, leaving the unmonitored areas in network and leading to the problem of energy hole. This paper investigates a variety of strategies to avoid the energy hole, such as communication power control, data aggregation, nonuniform energy distribution, mobile node auxiliary and clustering. The analysis and comparison of different strategies are given and the advantages and disadvantage of them are discussed in this paper.

关键词： wireless sensor networks energy balance energy hole network lifetime

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A Energy Balanced Deployment for Linear Wireless Sensor Networks

A Energy Balanced Deployment for Linear Wireless Sensor Netw...

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2011 International Conference on Computer Science and Network Technology(2011计算机科学与网络技术国际会议 ICCSNT 2011)

作者： Zhengjie Wang Xiaoguang Zhao Xu Qian College of Information and Electrical Engineering Shandong University of Science and Technology Qi State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese School of Mechanical Electronic & Info. Engineering China University of Mining & Technology (Beijin

ISBN: (纸本)9781457715860

Linear wireless sensor networks are characterized by a linear topology and multihop forwarding patterns. Sensors closer to the base station are usually required to forward a large amount of traffic for sensors farther from the base station, leading to the environment cannot be effectively monitored. The energy consumption balance is achieved in the paper by adjusting the distance between nodes. The distance of nodes near the base station become short because they have to forward the more traffic. The node deployment is converted to optimization problems of distance distribution between nodes. The network lifetime under different number of forwarding region is discussed. Simulation results show that this deployment strategy obtains the energy consumption balance.

关键词： wireless sensor networks optimal communication distance energy consumption balance distance optimal

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Agent-based traffic simulation and traffic signal timing optimization with GPU

Agent-based traffic simulation and traffic signal timing opt...

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International Conference on Intelligent Transportation

作者： Zhen Shen Kai Wang Fenghua Zhu State Key Laboratory of Intelligent Control and Management of Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences (CAS) Beijing China Center of Military Computational Experiments and Parallel Systems Technology and College of Mechatronics Engineering and Automation National University of Defense Technology Changsha Hunan China

With the advantage of simulating the details of a transportation system, the “microsimulation” of a traffic system has long been a hot topic in the Intelligent Transportation systems (ITS) research. The Cellular Automata (CA) and the Multi-Agent System (MAS) modeling are two typical methods for the traffic microsimulation. However, the computing burden for the microsimulation and the optimization based on it is usually very heavy. In recent years the Graphics Processing Units (GPUs) have been applied successfully in many areas for parallel computing. Compared with the traditional CPU cluster, GPU has an obvious advantage of low cost of hardware and electricity consumption. In this paper we build an MAS model for a road network of four signalized intersections and we use a Genetic Algorithm (GA) to optimize the traffic signal timing with the objective of maximizing the number of the vehicles leaving the network in a given period of time. Both the simulation and the optimization are accelerated by GPU and a speedup by a factor of 195 is obtained. In the future we will extend the work to large scale road networks.

关键词： Graphics processing unit Vehicles Roads Optimization Computational modeling Genetic algorithms Timing

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Algorithm design of traffic incident automatic detection based on mobile detection

Algorithm design of traffic incident automatic detection bas...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Zi Zhang Xiaoli Lin Bin Hu Communications Commission of Guangzhou Municipality Guangzhou Communication Information Construction Investment and Operation Company Limited Guangzhou China Transportation Management General Station of Guangzhou Haizhu Guangzhou China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy and Sciences Beijing China

Most researches of traffic incident auto-detection are based on the data from fixed detectors, which are limited by costs and position. In order to resolve this problem, existing algorithms of traffic incident automatic detection are analyzed and compared, and an algorithm of traffic incident auto-detection are provided based on mobile-detection technology. The traffic data are grouped in 5-min intervals, analyzed by a three-layer BP neural network, and utilized for traffic incident detection. 16 traffic incidents of different locations and different levels are modeled in the simulation experiment based on VISSIM, and detection rate, false alarm rate and average detection time are adopted as indicators to evaluate the algorithm. Finally, the algorithm is proved to be effective and applicable in practice.

关键词： Three dimensional displays Bayesian methods Detectors

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Spatio-temporal evolution of Beijing 2003 SARS epidemic

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Science China Earth Sciences 2010年第7期53卷 1017-1028页

作者： CAO ZhiDong ZENG DaJun ZHENG XiaoLong WANG QuanYi WANG FeiYue WANG JinFeng WANG XiaoLi Key Laboratory of Complex Systems and Intelligence Science Institute of AutomationChinese Academy of SciencesBeijing 100190China Beijing Center for Disease Control and Prevention Beijing 100013China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China

Studying spatio-temporal evolution of epidemics can uncover important aspects of interaction among people, infectious diseases, and the environment, providing useful insights and modeling support to facilitate public health response and possibly prevention measures. This paper presents an empirical spatio-temporal analysis of epidemiological data concerning 2321 SARS-infected patients in Beijing in 2003. We mapped the SARS morbidity data with the spatial data resolution at the level of street and township. Two smoothing methods, Bayesian adjustment and spatial smoothing, were applied to identify the spatial risks and spatial transmission trends. Furthermore, we explored various spatial patterns and spatio-temporal evolution of Beijing 2003 SARS epidemic using spatial statistics such as Moran’s I and LISA. Part of this study is targeted at evaluating the effectiveness of public health control measures implemented during the SARS epidemic. The main findings are as follows. (1) The diffusion speed of SARS in the northwest-southeast direction is weaker than that in northeast-southwest direction. (2) SARS’s spread risk is positively spatially associated and the strength of this spatial association has experienced changes from weak to strong and then back to weak during the lifetime of the Beijing SARS epidemic. (3) Two spatial clusters of disease cases are identified: one in the city center and the other in the eastern suburban area. These two clusters followed different evolutionary paths but interacted with each other as well. (4) Although the government missed the opportunity to contain the early outbreak of SARS in March 2003, the response strategies implemented after the mid of April were effective. These response measures not only controlled the growth of the disease cases, but also mitigated the spatial diffusion.

关键词： severe acute respiratory syndrome (SARS) Beijing morbidity rate spatial analysis spatio-temporal evolution control measures

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Study of Direction Probability and Algorithm of Improved Marriage in Honey Bees Optimization for Weapon Network System

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Defence Technology（防务技术） 2009年第2期5卷 152-157页

作者：杨晨光涂序彦陈杰 Systems Engineering Research Institute China State Shipbuilding Corporation Department of Automation School of Information Science and Technology Beijing Institute of Technology Ministry of Education of Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

To solve the weapon network system optimization problem against small raid objects with low attitude,the concept of direction probability and a new evaluation index system are *** calculating the whole damaging probability that changes with the defending angle,the efficiency of the whole weapon network system can be subtly *** such method,we can avoid the inconformity of the description obtained from the traditional index *** new indexes are also proposed,*** index,overlap index and cover index,which help manage the relationship among several *** normalizing the computation results with the Sigmoid function,the matching problem between the optimization algorithm and indexes is well ***,the algorithm of improved marriage in honey bees optimization that proposed in our previous work is applied to optimize the embattlement *** is carried out to show the efficiency of the proposed indexes and the optimization algorithm.

关键词：网络系统优化问题破坏概率算法改进核武器蜜蜂婚姻 Sigmoid函数

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Qualitative control for mobile robot navigation based on reinforcement learning and grey system

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Mediterranean Journal of Measurement and control 2008年第1期4卷 1-7页

作者： Chen, Chunlin Dong, Daoyi Chen, Zonghai Wang, Haibo School of Management and Engineering Nanjing University Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Key Laboratory of Systems and Control Institute of Systems Science Beijing China Department of Automation University of Science and Technology of China China

A qualitative control method using reinforcement learning (RL) and grey system is developed for mobile robot navigation in an unknown environment. New representation and computation mechanisms are key approaches for learning and control problems with incomplete information or in large probabilistic environments. In this paper, the uncertainties in sensor information and qualitative localization are represented using grey systems. Traditional RL methods are also combined with grey theory for mobile robot navigation control and a new grey reinforcement learning (GRL) method is proposed to solve complex problems where environment information is incomplete and grey models are constructed through representing incomplete information with grey algebra. The experimental results verify the effectiveness and superiority of the qualitative control system and the presented approaches also show alternative ways for the measurement and learning control problems with incomplete information of the environment. Copyright © 2008 SoftMotor Ltd.

关键词： Mobile robots

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Smart Health 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Xiaolong Zheng Daniel Zeng Hsinchun Chen Yong Zhang Chunxiao Xing Daniel B. Neill

ISBN: (数字)9783319084169

ISBN: (纸本)9783319084152

This book constitutes the refereed proceedings of the International Conference for Smart Health, ICSH 2014, held in Beijing, China, in July 2014. The 21 papers presented together with 4 extended abstracts were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on information sharing, integrating and extraction; health data analysis and management; clinical and medical data mining; and clinical practice and medical monitoring.

关键词： Health Informatics Database management Information systems Applications (incl. Internet) Data Mining and Knowledge Discovery Information Storage and Retrieval

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Advances in Brain Inspired Cognitive systems 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Derong Liu Dongbin Zhao Cesare Alippi Amir Hussain

ISBN: (数字)9783642387869

ISBN: (纸本)9783642387852

This book constitutes the refereed proceedings of the 6th International Conference on Brain Inspired Cognitive systems, BICS 2013, held in Beijing, China in June 2013. The 45 high-quality papers presented were carefully reviewed and selected from 68 submissions. BICS 2013 aims to provide a high-level international forum for scientists, engineers, and educators to present the state of the art of brain inspired cognitive systems research and applications in diverse fields.

关键词： Artificial Intelligence Information systems Applications (incl. Internet) Database management Information Storage and Retrieval Pattern Recognition Computation by Abstract Devices

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