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IEEE/RSJ International Conference on intelligent Robots and systems, IROS 2015

作者： Yi, Yang Geng, Zhou Zhang, Jianqing Cheng, Siyuan Fu, Mengyin School of Automation and State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9781479999941

This paper describes a novel amphibious robot, which adopts a dual-swing-legs propulsion mechanism, proposing a new locomotion mode. The robot is called FroBot, since its structure and locomotion are similar to frogs. Our inspiration comes from the frog scooter and breaststroke. Based on its swing leg mechanism, an unusual universal wheel structure is used to generate propulsion on land, while a pair of flexible caudal fins functions like the foot flippers of a frog to generate similar propulsion underwater. On the basis of the prototype design and the dynamic model of the robot, some locomotion control simulations and experiments were conducted for the purpose of adjusting the parameters that affect the propulsion of the robot. Finally, a series of underwater experiments were performed to verify the design feasibility of FroBot and the rationality of the control algorithm. © 2015 IEEE.

关键词： Propulsion

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Performance evaluation of the deep learning approach for traffic flow prediction at different times

Performance evaluation of the deep learning approach for tra...

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

作者： Yanjie Duan Yisheng Lv Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao Shandong China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781509029280

Traffic flow prediction is very important in the deployment of intelligent transportation system. Based on our previous research on deep learning approach for traffic data prediction, we further evaluates the performance of the SAE model for traffic flow prediction at daytime and nighttime. Through 250 experimental tasks training a SAE model and evaluating its performance at daytime and nighttime with 3 different criteria, we obtain the best combination of hyper parameters for each criterion at different times on weekday and non-weekday, respectively. Experimental results show that the MAE and RMSE at daytime are larger than that at nighttime, while the MRE at daytime are smaller than that at nighttime. For different criteria, the hyper parameters of the SAE model should vary accordingly. The results in this paper indicate that in real applications, traffic flow prediction using the deep learning approach can be a combination of multiple SAE models with different parameters suitable for different periods, which is of significance in future research.

关键词： Predictive models Machine learning Training Data models Roads Mathematical model Prediction algorithms

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Long short-term memory model for traffic congestion prediction with online open data

Long short-term memory model for traffic congestion predicti...

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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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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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A Simple and Effective Method For the Use of Chemical Accident Cases

A Simple and Effective Method For the Use of Chemical Accide...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Sifeng.Jing Xiwei.Liu Chuanzhong.Xu Institute of Smart Education Systems Qingdao Academy of Intelligent Industries The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Refinery No.2 Petro China Fushun Petrochemical Company

past chemical industry accident cases include volume valuable information like precursor, equipment involved, relevant causes and experiences of emergence response. In-depth analysis and fully utilization of these information play an important decision-making role in controlling risk and enhancing safety performance in chemical industry. In this work, a survey of use of accident data is conducted around the world and the result shows that the detailed use of these information play an important role in preventing accidents. However, in china there much more needs to be done in the application of accident data. According to the needs of safety management of chemical plants, a simple and effective method of the use of chemical accident cases is proposed based on collecting and analyzing of a large number of chemical accident cases. And finally, a utilization system of chemical industry accident cases is implemented through Microsoft access 2010. The result shows that the system can realize the effective management and use of past chemical accident information.

关键词： chemical accident cases use of information database fuzzy query chemical safety performance

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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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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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A simple and effective method for the use of chemical accident cases

A simple and effective method for the use of chemical accide...

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

作者： Sifeng Jing Xiwei Liu Chuanzhong Xu Institute of Smart Education Systems Qingdao Academy of Intelligent Industries The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Refinery No.2 PetroChina Fushun Petrochemical Company Fushun China

ISBN: (纸本)9781509029280

Past chemical industry accident cases include volume valuable information like precursor, equipment involved, relevant causes and experiences of emergence response. In-depth analysis and fully utilization of these information play an important decision-making role in controlling risk and enhancing safety performance in chemical industry. In this work, a survey of use of accident data is conducted around the world and the result shows that the detailed use of these information play an important role in preventing accidents. However, in China there much more needs to be done in the application of accident data. According to the needs of safety management of chemical plants, a simple and effective method of the use of chemical accident cases is proposed based on collecting and analyzing of a large number of chemical accident cases. And finally, a utilization system of chemical industry accident cases is implemented through Microsoft access 2010. The result shows that the system can realize the effective management and use of past chemical accident information.

关键词： Accidents Chemicals Databases Petrochemicals Chemical industry Safety management

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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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Parameter identification of plant growth models with stochastic development

Parameter identification of plant growth models with stochas...

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International Conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Applications (FSPMA)

作者： Mengzhen Kang Jing Hua Philippe de Reffye Marc Jaeger Qingdao Academy of Intelligent Sciences Qingdao China State Key Laboratory of Management and Control for Complex Systems CASIA Beijing China AMAP Unit CIRAD Montpellier Languedoc-Roussillon FR AMAP Unit CIRAD Montpellier Languedoc-Roussillon France LIRMM ICAR University of Montpellier France

ISBN: (纸本)9781509016600

Plant architectures generally display structural variations among individuals. Stochastic FSPMs have been developed to capture such feature, but calibrating such models is a challenging issue. For GreenLab model, parameter identification has been achieved on several crops and trees, but the estimation of functional parameters is mostly limited to plants with deterministic development. In this work, we propose a methodological framework allowing the efficient FSPM parameter estimation for stochastic ramified plants. We focus on the randomness in three kinds of meristem activities in plant development: growth, death and branching. Concepts of organic series and potential structure are introduced to build the fitting target as well as corresponding model output. We show that, with a limited set of sampled plants (here from simulation), using a few organic series, the inverse method retrieves well the parameter values (the original parameter set being known here). Requiring the concept of physiological age and the assumption of common biomass pool, the proposed approach provides a solution of solving source-sink functions of complex plant architectures, with a novel simplified way of plant sampling. The proposed parameter estimation frame is promising, since this in silico process mimics the procedure of calibrating model for real plants in a stand. Estimating parameters on stochastic plant architectures opens a new range of coming applications.

关键词： Stochastic processes Biological systems Physiology Biological system modeling Computational modeling Vegetation Biomass

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