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International Conference on intelligent Transportation

作者： Yuan-yuan Chen Yisheng Lv Zhenjiang Li Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao Shandong China

ISBN: (纸本)9781509018901

Traffic congestion in metropolitan areas has become more and more serious. Over the past decades, many academic and industrial efforts have been made to alleviate this problem, among which providing accurate, timely and predictive traffic conditions is a promising approach. Nowadays, online open data have rich traffic related information. Typical such resources include official websites of traffic management and operations, web-based map services (like Google map), weather forecasting websites, and local events (sport games, music concerts, etc.) websites. In this paper, online open data are discussed to provide traffic related information. Traffic conditions collected from web based map services are used to demonstrate the feasibility. The stacked long short-term memory model, a kind of deep architecture, is used to learn and predict the patterns of traffic conditions. Experimental results show that the proposed model for traffic condition prediction has superior performance over multilayer perceptron model, decision tree model and support vector machine model.

关键词： Logic gates Predictive models Computer architecture Google Data mining Microprocessors Social network services

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Distributed formation stabilization for mobile agents using virtual tensegrity structures 34

Distributed formation stabilization for mobile agents using ...

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34th Chinese control Conference, CCC 2015

作者： Qingkai, Yang Ming, Cao Hao, Fang Jie, Chen Jie, Huang School of Automation Beijing Institute of Technology Beijing China Faculty of Mathematics and Natural Sciences ITM University of Groningen Groningen Netherlands Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

ISBN: (纸本)9789881563897

This paper investigates the distributed formation control problem for a group of mobile Euler-Lagrange agents to achieve global stabilization by using virtual tensegrity structures. Firstly, a systematic approach to design tensegrity frameworks is elaborately explained to confine the interaction relationships between agents, which allows us to obtain globally rigid frameworks. Then, based on virtual tensegrity frameworks, distributed control strategies are developed such that the mobile agents converge to the desired formation globally. The theoretical analysis is further validated through simulations. © 2015 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Euler-Lagrange dynamics Formation stabilization Global convergence Tensegrity structure

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Cloud control systems

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自动化学报 2015年第2期2卷 134-142页

作者： Xia Yuanqing the School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081

The concept of cloud control systems is discussed in this paper, which is an extension of networked control systems (NCSs). With the development of internet of things (IOT), the technology of NCSs has played a key role in IOT. At the same time, cloud computing is developed rapidly, which provides a perfect platform for big data processing, controller design and performance assessment. The research on cloud control systems will give new contribution to the control theory and applications in the near future.

关键词： Cloud control systems (NCSs) networked control systems cloud computing cyber-physical systems (CPSs) big data

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Cyber-physical-social System in intelligent Transportation

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IEEE/CAA Journal of Automatica Sinica 2015年第3期2卷 320-333页

作者： Gang Xiong Fenghua Zhu Xiwei Liu Xisong Dong Wuling Huang Songhang Chen Kai Zhao the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Science the Cloud Computing Center Chinese Academy of Sciences Qingdao Academy of Intelligent Industries Beijing Engineering Research Center for Intelligent Systems and Technology Institute of AutomationChinese Academy of Science

A cyber-physical system (CPS) is composed of a physical system and its corresponding cyber systems that are tightly fused at all scales and levels. CPS is helpful to improve the controllability, efficiency and reliability of a physical system, such as vehicle collision avoidance and zero-net energy buildings systems. It has become a hot R&D and practical area from US to EU and other countries. In fact, most of physical systems and their cyber systems are designed, built and used by human beings in the social and natural environments. So, social systems must be of the same importance as their CPSs. The indivisible cyber, physical and social parts constitute the cyber-physical-social system (CPSS), a typical complex system and it's a challengeable problem to control and manage it under traditional theories and methods. An artificial systems, computational experiments and parallel execution (ACP) methodology is introduced based on which data-driven models are applied to social system. Artificial systems, i.e., cyber systems, are applied for the equivalent description of physical-social system (PSS). Computational experiments are applied for control plan validation. And parallel execution finally realizes the stepwise control and management of CPSS. Finally, a CPSS-based intelligent transportation system (ITS) is discussed as a case study, and its architecture, three parts, and application are described in detail. © 2014 Chinese Association of Automation.

关键词： Amphibious vehicles complex networks Embedded systems intelligent systems Transportation

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Exploring Optimal Frequency Caps in Real Time Bidding Advertising

Exploring Optimal Frequency Caps in Real Time Bidding Advert...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Rui Qin Yong Yuan Fei-Yue Wang Beijing Engineering Research Center of Intelligent Systems and Technology Beijing China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China

ISBN: (纸本)9781509039371

Benefited from the high-speed development of Internet and the popularization of big data technology, Real Time Bidding (RTB) emerged and developed quickly, and has become one of the most important and popular model for online computational advertising. In the pay-per-impression based RTB advertising, frequency capping is undoubtedly one of the most crucial issues faced by advertisers and Demand Side Platforms (DSPs), since there are generally vast amount of ad requests in RTB markets, among which many may be triggered by the same target audience. As such, choosing the optimal frequency cap considering all the advertisers becomes a critical issue faced by DSPs. Considering that displaying one advertisement multiple number of times to the same user will diminish the advertising effect, we introduce the concept of discount factor and establish an optimization model of frequency capping to seek for the optimal frequency cap for each advertiser. We also design some experiments to validate our proposed model by utilizing the computational experiment approach, and the experimental results show that the optimal frequency cap can be influenced by the values of the discount factors, and higher value of the discount factor can deduce the advertising effect of larger frequency cap. Moreover, when the discount factors of the advertisers take different values, there also exists an optimal frequency cap, at which the advertisers can get the expected maximum revenue in the long run.

关键词： Advertising Digital signal processing Computational modeling Big data Time-frequency analysis Radio spectrum management Real-time systems

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Optimizing Market Segmentation Granularity in RTB Advertising: A Computational Experimental Study

Optimizing Market Segmentation Granularity in RTB Advertisin...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

ISBN: (纸本)9781509039371

Real Time Bidding (RTB) is a novel business model of online computational advertising with the integration of Internet economy and big data analysis. It can help advertisers achieve the precision marketing through the market segmentation strategies of Demand Side Platforms (DSPs). Based on a mathematical programming approach, this paper studied DSPs' strategies for market segmentation, and established a selection model of the granularity for segmenting RTB advertising markets. We proposed to validate our model using the computational experiment approach, and the experimental results show that: 1) with the increasing refinement of the market segmentation granularity, the total revenue has a tendency of a rise first followed by a decline, 2) the optimal granularity of market segmentation will be significantly influenced by the number of advertisers on the DSP, but less influenced by the number of ad requests. Our findings show the crucial role of market segmentation on the RTB advertising effect, and indicate that the DSPs should adjust their market segmentation strategies according to their total number of advertisers. Our findings also highlight the importance of advertisers as well as the characteristics of the target audiences in DSPs' market segmentation decisions.

关键词： Digital signal processing Computational modeling Advertising Numerical models Big data complex systems Automation

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Plant growth architecture and production dynamics : A set of e-learning resources

Plant growth architecture and production dynamics : A set of...

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2016 IEEE International Conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Applications, FSPMA 2016

作者： Jaeger, Marc De Reffye, Philippe Sabatier, Sylvie Caraglio, Yves Krit, Hatem Lafond, Marie-Helene Letort, Veronique Heuvelink, Ep Motisi, Matacha Zhang, BaoGui Kang, Mengzhen CIRAD AMAP Unit Montpellier34398 France University of Montpellier LIRMM ICAR Montpellier34095 France CentraleSupélec MAS Châtenay-Malabry92290 France WURL HPC Group Wageningen6700AA Netherlands CIRAD Pest and Disease Unit Montpellier34398 France Key Laboratory of Plant-Soil Interactions College of Resources and Environment China Agricultural University Beijing100193 China State Key Laboratory of Management and Control for Complex Systems LIAMA CASIA Beijing100190 China Qingdao Academy of Intelligent Sciences Qingdao266109 China

ISBN: (纸本)9781509016594

FSPM Plant and crop models are popular in the research community and there is increasing interest in their applications, from yield prediction to crop management optimization. A wide range of approaches and their software implementation can be found in the literature, with a large diversity in modelling scale (from plant organ to plot levels) and scope (structural, functional or both), as well as generic or specific aim. However, most of these approaches rely on similar key assumptions and methods related to different disciplines: Botany for plant structure, eco-physiology for production, statistics and dynamic system theory for parameter identification and estimation. Web disseminated plant and crop models learning supports are not numerous, often specific, and partial. We present here a set of e-learning resources, named 'Plant growth architecture and production dynamics' which describes the main notions from plant morphology and architecture, eco-physiology and applied mathematics necessary to the understanding of most plant and crop models, and their typology. In this paper, after an overview of existing learning resources on plant and crop modelling which, we believe, might be of interest for the whole research community, we present the proposed resource, which uses the GreenLab model as illustration, organized as follows: •Five standalone introductive disciplinary resources: Botanical notions, assumptions in eco-physiology, basis in data processing, introduction to models, introduction to GreenLab •An FSPM example in more details: GreenLab positioning, its basis, structure modelling, production modelling, and applications including model fitting and a study case •Tools: Inline (for structure analysis and statistics), online (access to fitters for instance) and access to download simulators and their documentation •Glossary, bibliography, web site collection, and a pedagogic kit for instructors Supported by the French Sustainable Development Virtual University

关键词： Glossaries

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TDMA based IEEE 802.15.4 for Simple/Secured Low Latency Deterministic Networked control systems

TDMA based IEEE 802.15.4 for Simple/Secured Low Latency Dete...

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第三十四届中国控制会议

作者： Mashood Anwar Yuanqing Xia School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology

ISBN: (纸本)9781467374439

In this paper, we propose a time division multiple access(TDMA) based protocol that works on slightly modified IEEE802.15.4 network in star topology for secured and unsecured low latency deterministic networks(LLDN) for industrial control systems. This protocol ensures total superframe time as low as ten milliseconds as compared to minimum possible superframe time of 15.36 milliseconds. In these networks, Each end device transmits its data frame in their allotted timeslot. The timeslot and inter timeslot spacing is optimized for channel bandwidth utilization and reliable data frame exchange. While this TDMA based protocol eliminates the risk of frame collisions to great extent, MAC sub-layer tweaking improves the non-determinism of the network and increases its bandwidth efficiency. We also investigate the security impact on the performance of LLDN. A mathematical model is developed that takes empirical values as input and predicts the worst case arrival times of network devices at coordinator. Experiments were conducted to evaluate the suggested protocol and mathematical model.

关键词： IEEE 802.15.4,Networked control system,Low latency deterministic networks(LLDN),Medium access control(MAC),TDMA,security

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ACP-based social computing and parallel intelligence： Societies 5.0 and beyond

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CAAI Transactions on Intelligence Technology 2016年第4期1卷 377-393页

作者： XiaoWang Lingxi Li Yong Yuan Peijun Ye Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Qingduo Academy of Intelligent Industries Qingduo 266100 China Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University-Purdue University Indianapolis Indianapolis IN 46202 USA

Social computing, as the technical foundation of future computational smart societies, has the potential to improve the effectiveness of opensource big data usage, systematically integrate a variety of elements including time, human, resources, scenarios, and organizations in the current cyber-physical-social world, and establish a novel social structure with fair information, equal rights, and a flat configuration. Meanwhile, considering the big modeling gap between the model world and the physical world, the concept of parallel intelligence is introduced. With the help of software-defined everything, parallel intelligence bridges the big modeling gap by means of constructing artificial systems where computational experiments can be implemented to verify social policies, economic strategies, and even military operations. Artificial systems play the role of ＂social laboratories＂ in which decisions are computed before they are executed in our physical society. Afterwards, decisions with the expected outputs are executed in parallel in both the artificial and physical systems to interactively sense, compute, evaluate and adjust system behaviors in real-time, leading system behaviors in the physical system converging to those proven to be optimal in the artificial ones. Thus, the smart guidance and management for our society can be achieved.

关键词： Social computing Societies 5.0 Parallel intelligence Knowledge automation Cyber-physical-social system Artificial societies Computational ex-periments Parallel execution

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SH–STF: a Novel Adaptive Filter and its Application in SINS/GPS/DVS Integrated Navigation

SH–STF: a Novel Adaptive Filter and its Application in SINS...

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第三十四届中国控制会议

作者： Liping Yan Yuanqing Xia Mengyin Fu Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

ISBN: (纸本)9781467374439

This paper is concerned with adaptive filter and its application in SINS/GPS/DVS integrated navigation. A novel adaptive filter, namely, SH–STF, is presented by combining the Sage–Husa(SH) adaptive filter with the strong tracking filter(STF). For multirate sampling dynamic system and in consideration of observations randomly missing, SH–STF is applied to data fusion and SINS/GPS/DVS integrated navigation. Simulation results show the feasibility and effectiveness of the presented algorithm.

关键词： integrated navigation,Sage–Husa adaptive filter,strong tracking filter,data fusion

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