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

作者： Yu-Ling Hu Ding Wen Xi-Wei Liu School of Electric and Information Engineering Beijing University of Civil Engineering and Architecture Beijing China Beijing Key Laboratory of Automatic Control System School of Automation Beijing Institute of Technology Beijing China Research Center of Military Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha China Institute of Automation Chinese Academy and Sciences Beijing China

Because the structure and function of a high-rise building is complex and the density of occupants in it is high, fire safety is still a worldwide difficult problem. Safety and timely evacuation is an important issue under fire in the high-rise buildings. Because it is impossible in fact to do experiments about fire safety evacuation in high-rise buildings, in this paper, a research framework based on the artificial system, computational experiments, and parallel excution (ACP) theory is proposed. First, an evacuation process is considered to compose of two stages including pre-evacuation stage and evacuation stage. Second, artifical men with recognition functions based agent technology is proposed. Finally, computational experiments are designed by using an orthogonal experiment table, and experiment procedure of pre-evacuation stage is given. The idea of systimatic research about the influence of fire control facilities to evacuation is also proposed.

关键词： Fires Computational modeling Buildings

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Case-based safety assessment of thermal power plants: A framework

Case-based safety assessment of thermal power plants: A fram...

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International Conference on Business Management and Electronic information (BMEI)

作者： Changyong Liang Dongxiao Gu Isabelle Bichindaritz Chunrong Zuo Fei Cheng School of Management Hefei University of Technology Hefei Anhui China Research Center of Intelligent Decision Making and Information System Technologies Ministry of Education of China Hefei Anhui China Department of Computer Science University of Illinois Chicago Chicago IL USA Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education of China Hefei Anhui China Institute of Technology University of Washington Tacoma WA USA

Security assessment of Thermal Power Plants (TPPs) is one of the important means to guarantee the safety of production in thermal power production enterprises. Essentially, the evaluation of power plant systems relies to a large extent on the knowledge and length of experience of the experts. Therefore in this domain Case-Based Reasoning (CBR) is introduced for the security assessment of TPPs since this methodology models expertise through experience management. Taking the management system of TPPs as breakthrough point, this paper presents a case-based approach for the security assessment decision support of TPPs (SATPP). First, this paper reviews commonly used approaches for TPPs security assessment and the current general evaluation process of TPPs security assessment. Then a framework for the Management system Security Assessment of Thermal Power Plants (MSSATPP) is constructed and an Intelligent Decision Support system for MSSATPP (IDSS-MSSATPP) is functionally designed. MSSATPP involves several key technologies and methods such as knowledge representation and case matching.

关键词： Security Safety Production Power generation Power systems Decision making Indexes

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Robust Filtering for Networked systems with Random Transmission Delays and Packet Dropouts

Robust Filtering for Networked Systems with Random Transmiss...

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2011 American control Conference (ACC)

作者： Yunze Cai Hua O. Wang Kazuo Tanaka Xiaoming Xu Department of Mechanical Engineering Boston University Boston MA USA Department of Automation and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiaotong University Shanghai China Department of Mechanical Systems and Intelligent Systems University of Electro-Communications Tokyo Japan Department of Automation Shanghai Jiaotong University Shanghai China University of Shanghai for Science and Technology Shanghai China

This paper addresses a robust H_(infinity) filtering problem for networked systems that are subject to both random transmission delays and packet dropouts. To start with, a data transmission model is established by employing random series with Bernoulli distributions. A sufficient condition for robust stability with H_(infinity) constraints is derived for the filtering error system. The robust filter is designed in terms of the feasibility of a linear matrix inequality (LMI). The numerical examples are provided to show the effectiveness of the data transmission model and the proposed filtering method.

关键词： Delay Filtering Robustness Data models Symmetric matrices Hidden Markov models Markov processes

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Electricity price forecasting using neural networks trained with entropic criterion

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7th International Symposium on Neural Networks, ISNN 2010

作者： Zhang, Jianhua Wang, Jingyue Wang, Rui Hou, Guolian Beijing Key Laboratory of Industrial Process Measurement and Control New Technology and System North China Electric Power University Beijing 102206 China

ISBN: (纸本)9783642129896

Accurate electricity price forecasting is critical to market participants in wholesale electricity markets. The problem becomes more complex because the acquired data series are non-linear and non-Gaussian. In this paper, Multi Layer Perceptrons (MLP) trained with minimizing error entropy (MEE) algorithm is utilized to forecast electricity price. Compared with the conventional MLP with mean square error (MSE) criterion, the proposed approach can achieve better performance in simulated examples. © 2010 Springer-Verlag Berlin Heidelberg.

关键词： Entropy

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Containment control of networked Lagrange systems with group dispersion and cohesion behaviors

Containment control of networked Lagrange systems with group...

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Chinese control Conference (CCC)

作者： Ziyang Meng Zongli Lin Wei Ren Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville 22904-4743 U.S.A. Department of Electrical and Computer Engineering Utah State University Logan 84322 U.S.A.

In this paper, distributed containment control with group dispersion and cohesion behaviors are discussed for a group of Lagrange systems. Both the cases of constant leaders' generalized coordinate derivatives and time-varying leaders' generalized coordinate derivatives are considered. The proposed control algorithms are shown to obtain velocity matching, connectivity maintenance and collision avoidance. In addition, the sum of the steady-state distances between followers and the convex hull formed by the leaders is shown to be bounded and this bound is explicitly given.

关键词： Lead Dispersion Topology Sensors Laplace equations Maintenance engineering Algorithm design and analysis

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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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Analyzing and correlating security events using state machine

Analyzing and correlating security events using state machin...

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10th IEEE International Conference on Computer and information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and systems, ICESS-2010, 10th IEEE Int. Conf. Scalable Computing and Communications, ScalCom-2010

作者： Feng, Xuewei Wang, Dongxia Zeng, Jiemei Ma, Guoqing Li, Jin National Key Laboratory of Science and Technology on Information System Security Beijing Institute of System Engineer Beijing 100101 China Beijing Aerospace Control Center Beijing 100296 China

ISBN: (纸本)9780769541082

It is unfeasible to analyze the security events by the manual way for the security manager, because the number of the events is huge and the information contained in the events is meaningless. After analyzing the existing algorithms of security events correlation, we propose an attack scenario reconstruction technology based on state machine. The processes of attackers intruding into the cyberspace can be restored and the more comprehensive attack scenario description information will be generated using this technology. This working lets the security manager more comfy. The state machine based attack scenario reconstruction technology processes security events using clustering analysis and causal analysis concurrently, it builds a correlation state machine in memory for every attack scenario tree which is predefined by the security manager, when security events are coming, the certain state machines will process them, if the condition is satisfied, an attack scenario description information will be generated and then sent to the security manager. The correlating technology based on state machine is more timely and accurately, and at last, we use the DARPA2000 Intrusion Scenario Specific Data Sets to validate the technology, the experiment results show that it is feasible to analyze security events using the technology we proposed. © 2010 IEEE.

关键词： Managers

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Estimation of component concentrations of sodium aluminate solution via PLS and Hammerstein recurrent neural networks

Estimation of component concentrations of sodium aluminate s...

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International Workshop on Advanced Computational Intelligence

作者： Wang, Wei Zhao, Lijie Chai, Tianyou Yu, Wen Key Laboratory of Integrated Automation of Process Industry Ministry of Education Northeastern University China Key Laboratory of Integrated Automation of Process Industry Information Engineering School Ministry of Education South Africa Departamento de Control Automatico CINVESTAV-IPN Mexico D.F. Mexico

ISBN: (纸本)9781424463343

In this paper, a new on-line soft sensing method is proposed for component concentrations of sodium aluminate solution. With this sensing strategy, real-time control and optimization can be realized in aluminate production plants. Several advance techniques are used, such as PLS (Partial Least Squares), Hammerstein model, recurrent neural networks and least square algorithm. Industrial experiment results show that the proposed soft sensing algorithm is effective.

关键词： Recurrent neural networks

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Design and realization of a remote monitoring and diagnosis and prediction system for large rotating machinery

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中国高等学校学术文摘·机械工程 2010年第2期5卷 165-170页

作者： Shaohong WANG Tao CHEN Jianghong SUN School of Mechanical Vehicular Engineering Beijing Institute of Technology Beijing 100081 China Beijing Key Laboratory on Measurement and Control of Mechanical and Electrical System Beijing Information Science & Technology University Beijing 100192 China

Traditional on-site fault diagnosis means cannot meet the needs of large rotating machinery for its performance and complexity. Remote monitoring and diagnosis technology is a new fault diagnosis mode combining computer technology, communication technology, and fault diagnosis technology. The designed remote monitoring and diagnosis and prediction system for large rotating machinery integrates the distributed resources in different places and breaks through shortcomings as the offline and decentralized information. The system can make further implementation of equipment prediction technology research based on condition monitoring and fault diagnosis, provide on-site analysis results, and carry out online actual verification of the results. The system monitors real-time condition of the equipment and achieves early fault prediction with great significance to guarantee safe operation, saves maintenance costs, and improves utilization and management of the equipment.

关键词： large rotating machinery remote monitoring fault diagnosis prediction system

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Network management in WirelessHART network for industry application

Network management in WirelessHART network for industry appl...

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yun, Zuo Zhihao, Ling Luming, Liu School of Information Science and Engineering East China University of Science and Technology Shanghai China Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education Shanghai China

ISBN: (纸本)9781424437092

The WirelessHART network is an emerging technology which aims at application in industry. The control network in industry always consists of many end devices and the environment is hash, so the network management of WirelessHART is very critical. This paper first introduced the wireless sensor network management mode and the critical techniques in WirelessHART network. Following that, network management in WirelessHART was analyzed and the solutions of some challenges were proposed. Finally it gave the expectation of WirelessHART technology. © 2010 IEEE.

关键词： Network management

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