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International Conference on intelligent Transportation

作者： Yujie Dai Jinzong Hu Dongbin Zhao Fenghua Zhu State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences (CAS) Beijing China Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences (CAS) China

Traffic congestion leads to problems like delays, decreasing flow rate, and higher fuel consumption. Consequently, keeping traffic moving as efficiently as possible is not only important to economy but also important to environment. Traffic system is a large complex nonlinear stochastic system. Traditional mathematical methods have some limitations when they are applied in traffic control. Thus, computational intelligence (CI) technologies gain more and more attentions. Neural Networks (NNs) is a well developed CI technology with lots of promising applications in traffic signal control (TSC). In this paper, a neural network (NN) based signal controller is designed to control the traffic lights in an urban traffic road network. Scenarios of simulation are conducted under a microscopic traffic simulation software. Several criterions are collected. Results demonstrate that through online reinforcement training the controllers obtain better control effects than the widely used pre-time and actuated methods under various traffic conditions.

关键词： Artificial neural networks Training Vehicles Roads Software Real time systems Learning systems

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Development of a Tetris Playing Robot controlled by KNR

Development of a Tetris Playing Robot Controlled by KNR

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IEEE International Conference on Mechatronics and Automation

作者： Ming Wang Yanlu Zhang Huifang Dong Xu Li Junzhi Yu Department of Information and Electrical Engineering University of Shandong Jianzhu University Jinan China Department of Intelligent Robotics State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Robot plays an increasingly important role in daily life. This paper presents a vision-based wheeled robot for playing Tetris. How to control the robot is elaborated at length in this paper. The robot adopted a KNR controller as its core controller. With a CCD sensor, it identified colored blocks, lines and the destination. All algorithms are programed with LabVIEW. The experiments and the contest validated the effectiveness of the proposed vision-based wheeled robot system.

关键词： Mobile robots Cameras Robot sensing systems Image color analysis Servomotors Robot kinematics

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A Process Simulation-Based Quantitative HAZOP Analysis Method

A Process Simulation-Based Quantitative HAZOP Analysis Metho...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Jianlong Chen Xiwei Liu Sifeng Jing Gang Xiong Xiuqin Shang Changjian Cheng The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Chemical Engineering and the Environment Beijing Institute of Technology Institute of Smart Education Systems Qingdao Academy of Intelligent Industries

Hazard and operability(HAZOP) methodology is an important Process Hazard Analysis(PHA) technique for ensuring safety production in chemical industry. Due to the lacks of accuracy and reliability in manual HAZOP analysis, the quantitative HAZOP analysis has gained more and more attention. In this work, a process simulation-based HAZOP analysis method and its flow chart are proposed. And the proposed method is applied to a steam generation subsystem in an ethylene pyrolysis unit on a dynamic process simulation platform. All deviation parameters of system can be calculated and described quantitatively. The case study shows the proposed method is useful for the effective risk prevention and control measures in a chemical process.

关键词： Quantitative HAZOP process simulation Process Hazard Analysis

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Theoretical Study of Millimeter Wave Attenuation in Particulate Environment

Theoretical Study of Millimeter Wave Attenuation in Particul...

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UK, Europe, China Millimeter Waves and THz Technology Workshop (UCMMT)

作者： Xiaoming Liu Yixin Zhou Tao Qi Lu Gan Xiaofan Yang School of Physics and Electronic Information Anhui Normal University Anhui Provincial Engineering Laboratory on Information Fusion and Control for Intelligent Robot Wuhu Anhui China State Key Laboratory of Complex Electromagnetic Environment Effects on Electronic and Information System Luoyang Henan China

ISBN: (数字)9781728129938

ISBN: (纸本)9781728129945

Particulate environment is frequently encountered in the millimeter wave propagation path. The particles usually produce scattering and absorption to the millimeter wave. Unfortunately, these particles usually have different size, ingredients and even a mixture of many elements. This paper presents a preliminary study of the attenuation of particles on millimeter wave transmission. The dielectric property of water sand and ice were also discussed. The study was conducted at 110 GHz and 220 GHz. Calculation was based on the Mie theory. A full wave simulation was also conducted to better understand the attenuation effect.

关键词： Millimeter wave technology Attenuation Millimeter wave communication Dielectrics Electromagnetic scattering Ice

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3D Deep Learning for 3D Printing of Tooth Model

3D Deep Learning for 3D Printing of Tooth Model

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

作者： Yiwen Liu Xiuqin Shang Zhen Shen Bin Hu Zhihai Wang Gang Xiong Faculty of Information The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing University of Technology Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China Faculty of Information Beijing University of Technology Beijing China

Recently, with the development of both 3D sensors and 3D virtual network that bring the needs of interaction with the real world, many 3D applications burst out. However, it is difficult to understanding these three-dimensional scenes with a fixed program. Then, a data-driven method is required to process these 3D data, which brings a strong demand of 3D Deep Learning in 3D data. Towards this goal, with an end-to-end deep learning, the experiment is based on PointNet++, a well proposed method for feature extraction. The experiment optimizes the network structure and parameters to improve the classification results. Finally, the network is applied to tooth model for classification and identification so that the dental model can be found from different perspectives.

关键词： Three-dimensional displays Deep learning Transforms Cameras Object segmentation Image segmentation Sensors

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An Embedded Co-AdaBoost and Its Application in Classification of Software Document Relation

An Embedded Co-AdaBoost and Its Application in Classificatio...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Jin Liu Juan Li Yuan Xie Jeff Lei Qiping Hu State Key Laboratory of Software Engineering Computer School Wuhan University China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation CAS China Department of Computer Science and Engineering University of Texas Arlington USA International School of Software Wuhan University China

To enhance classification performance by making use of easily available unlabelled data to overcome the scarcity of labelled data, this paper proposes an Embedded Co-Adaboost algorithm that integrates multi-view learning into the Adaboost learning framework and at the same time leverages the advantages of Co-training algorithm for performance enhancement. Experimental results demonstrate the effectiveness of the proposed algorithm in terms of the convergence rate, the accuracy, and the steady performance as compared to the original AdaBoost algorithm, without relying on redundant and sufficient feature sets. As a algorithm application in software engineering, the Embedded Co-AdaBoost has been applied to the classification of software document relations to improve the quality of the architecture design documents and the reusability of design knowledge.

关键词： Classification algorithms Training Software Accuracy Partitioning algorithms Software algorithms Convergence

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A new B2B platform based on cloud computing

A new B2B platform based on cloud computing

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Xiong, Gang Hou, Jiachen Dong, Xisong Nyberg, Timo R. State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan 523808 China Jiang Su China Sciences Intelligent Engineering Co. Ltd. Enterprise Academician Workstation 215000 China BIT Research Centre Aalto University Finland

ISBN: (纸本)9781467324007

With the fast development of Internet and its data scale, B2B (Business to Business), whose speed and high availability advantage is based on Internet, is eroding more and more market share of traditional business. In recent years, the new data processing technologies, such as cloud computing, assure the enhancement of computer's computing capacity;it has become possible for researchers to process and analyze the massive business data, including large scale customer data, and large scale commodity information. A new B2B platform frame, based on cloud computing with less running time and better response efficiency, is proposed here to promote transaction handle efficiency. By adoption of complex network theory and cloud computing technology, the new platform has been evaluated to decrease transaction handle time, and make more benefits. © 2012 IEEE.

关键词： complex networks

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Line-of-Sight Strategy-Based Path-Following system for a Multi-Joint Robotic Fish

Line-of-Sight Strategy-Based Path-Following System for a Mul...

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

作者： Shijie Dai Chao Zhou Zhengxing Wu Min Tan Junzhi Yu School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Naval Research Academy Beijing China State Key Laboratory for Turbulence and Complex System BIC-ESAT College of Engineering Peking University Beijing China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

This paper proposes a real-time path-following control system for a multi-joint robotic fish. The mechanical structure and dynamic model of the robotic fish for pathfollowing are first described. Then, the framework of the path-following control algorithm is established based on the built dynamic model, including a modified line-of-sight (LOS) guidance law, an active disturbance rejection control (ADRC)based heading controller and a proportional-integral-derivative (PID)-based speed controller. Specially, the modified LOS strategy is designed to select the tracking points and also provide the desired heading angle. Afterwards, to overcome systematic uncertainties and environmental disturbances, the ADRC method is adopted to design the heading controller. Meanwhile, the PID controller is also developed to maintain an appropriate swimming speed. Finally, simulations in both linear-and circular-path following are presented to validate the effectiveness of the proposed method.

关键词： Robots Robot kinematics Task analysis Real-time systems Oscillators Mathematical model Force

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Muscle-Synergy-Based Planning and Neural-Adaptive control for a Prosthetic Arm

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2021年第5期2卷 424-436页

作者： Li, Guoxin Li, Zhijun Li, Junjun Liu, Yueyue Qiao, Hong The Department of Automation University of Science and Technology of China Hefei230026 China The Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230026 China The School of Automation Science and Engineering South China University of Technology Guangzhou511442 China The State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Science Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The Center for Excellence in Brain Science and Intelligence Technology Institute of Neuroscience Chinese Academy of Science Shanghai200031 China

Upper limb loss has significant effects on the individual's quality of life. Artificial prosthetic limbs as an alternative to the lost limb are designed to allow amputees to regain motor function. Motion classification via extracted surface electromyogram (sEMG) signals is widely utilized to realize a friendly human-robot interface in the control of the prosthesis. However, limited classification of discrete motion patterns from sEMG prevents intuitive motor control. Thus, instead of using discrete patterns, decoding the human intention continuously from sEMG would significantly benefit the prosthesis control. In this article, we propose a muscle-synergy-based intention decoding and motion planning that can model a broad set of complex upper limb movements as a combination of motor primitives. A novel muscle activation-to-force mapping model is developed to detect muscular effort of the healthy side to drive the affected side. A neural-network-approximation-based controller is developed for the bionic neuroprosthetic arm to execute the movement. Operational experiments with prosthetic movement control were performed on four healthy participants and an upper limb amputee participant. Results of controlling prosthetic arm (0.94 ± 0.02 of R2 in the horizontal reaching tasks and 0.95 ± 0.01 in the vertical reaching tasks for the healthy subjects, 0.95 and 0.97 for the amputee) demonstrate that our control method could successfully capture human movement intention and effectively control the movement of prosthesis. Impact statement-Powered robotic prostheses have enabled individuals with limb amputations to regain motor function via motion intention decoding from extracting surface electromyogram signals. Most research works have provided human-robot interaction through motion classification obtained from pattern recognition using surface electromyogram signals and simple movement control. However, decoding the human intent continuously from surface electromyogram is con

关键词： Matrix algebra

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A two-stage fuzzy budget allocation model in search auctions

A two-stage fuzzy budget allocation model in search auctions

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

作者： Rui Qin Yong Yuan Juanjuan Li The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479960590

Budget optimization is an important issue faced by advertisers in search auctions, and has significant impact on the design of various advertising strategies. Given a limited budget on a search market during a certain period, an advertiser has to distribute her budget to a series of sequential temporal slots (i.e., days, weeks, or months), during which advertisers must avoid the budget being used up quickly, so as to keep the budget for potential clicks with better performance in the future. Considering the optimal budgets over these temporal slots as fuzzy variables, we establish a two-stage fuzzy budget allocation model, and use particle swarm optimization (PSO) algorithm to solve it in case when these optimal budgets are characterized by discrete fuzzy variables. We also conduct experiments to validate our model and algorithm. The experimental results show that our model can outperform other five budget allocation strategies in terms of reducing the revenue loss of the advertiser.

关键词： Artificial intelligence

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