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2014 IEEE International Conference on Service Operations and Logistics,and Informatics

作者： Kainan Cui Xiaolong Zheng The School of Electronic and Information Engineering Xi'an Jiaotong University The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

Understanding the strategies to optimize/suppress information spreads under intense competition could provide important insights in a broad range of settings including viral marketing,emergency response and information system ***,most of existing studies about competitive influence diffusion mainly focus on two-information competition *** date,the competitive influence maximization problem considering the mechanism of multi-information competition is still not well *** this paper,we conducted computational experiments to study the competitive influence maximization with multi-information competition *** applying an information diffusion model called limited attention model(LAM),we carried on two computational experiments to validate the model and investigate the relation between seed selection methods and the properties of information *** experimental results show that 1)the LAM model could reproduce the features of empirical distribution in Chinese social media;2)the eigenvector centrality-based heuristic is a reasonable seed selection method for competitive influence maximization *** results of this paper can provide significant potential implications for information system design and management.

关键词： computational experiments information diffusion competitive influence maximization social media

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An object recognition approach based on structural feature for cluttered indoor scene

An object recognition approach based on structural feature f...

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IEEE International Conference on Networking, Sensing and control

作者： Wenbo Yuan Zhiqiang Cao Peng Zhao Min Tan Yuequan Yang State Key Laboratory of Management and Control for Complex Systems Institute of Automation CAS Beijing China College of Information Engineering Yangzhou University Yangzhou China

In this paper, aiming at the indoor scene under monitoring by visual sensor network (VSN), an object recognition approach based on structural feature is presented. Firstly, we regard the output of existing line segment detector LSD with proper parameters as the preliminary extraction result and it still will be further restored and split. Then, we give an inference model based on structural features of object including line segment ontology characteristics and relative relationship between the line segments. Finally, the objects are recognized with position information through inference. The effectiveness of the approach is verified, and the results show that our approach does not rely on segmentation and has robustness on partial defect and structural deformation to some extent.

关键词： Image segmentation Robot sensing systems Monitoring Image recognition

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Model-free Adaptive Dynamic Programming for Optimal control of Discrete-time Affine Nonlinear System

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IFAC Proceedings Volumes 2014年第3期47卷 7049-7054页

作者： Zhongpu Xia Dongbin Zhao Huajin Tang The State Key Laboratory of Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Institute for Infocomm Research Agency for Science Technology and Research (A STAR) Singapore 138632

In this paper, a model-free and effective approach is proposed to solve infinite horizon optimal control problem for affine nonlinear systems based on adaptive dynamic programming technique. The developed approach, referred to as the actor-critic structure, employs two multilayer perceptron neural networks to approximate the state-action value function and the control policy, respectively. It uses data collected arbitrarily from any reasonable sampling distribution for policy iteration. In the policy evaluation phase, a novel objective function is defined for updating the critic network, and thus makes the critic network converge to the Bellman equation directly rather than iteratively. In the policy improvement phase, the action network is updated to minimize the outputs of the critic network. The two phases alternate until no more improvement of the control policy is observed, such that the optimal control policy is achieved. Two simulation examples are provided to show the effectiveness of the approach.

关键词： Model-free adaptive dynamic programming reinforcement learning policy iteration multilayer perceptron neural network

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IEEE Joint Intelligence and Security Informatics Conference (JISIC)

作者： Qingchao Kong Wenji Mao Daniel Zeng Lei Wang State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Department of Management Information Systems University of Arizona Tucson AZ USA College of Management and Economics Tianjin University Tianjin China

Web user's online interactive behavior with others often makes some user generated contents popular. The modeling and prediction of the popularity of online content are an important research issue for many key application domains. In this paper, we focus on one form of user generated content, forum threads, and their popularity prediction for public events security. To predict the popularity of forum threads, we first define the popularity prediction problem, and identify the dynamic factors that affect the popularity of forum threads. Based on the information of dynamic evolution at the early stage, we propose a popularity prediction algorithm which makes use of the locality property and combines multiple dynamic factors. The proposed algorithm is further evaluated using the Tianya forum dataset on the discussions of various public events. The experimental results show that, compared to the baseline methods, our method achieves relatively better performance in predicting the popularity of forum threads on public events security.

关键词： Heuristic algorithms Prediction algorithms Classification algorithms Instruction sets Message systems Predictive models Hidden Markov models

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Traffic light Time adjustment based on Interval type-2 fuzzy sets

Traffic light Time adjustment based on Interval type-2 fuzzy...

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2014 International Conference on Informative and Cybernetics for Computational Social systems(ICCSS2014)

作者： Zhen Gao Feng Hua Zhu Hong Mo College of Electrical and Information Engineering Changsha University of Science and Technology State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

According to the actual circumstance of the intersection,reasonably adjusting traffic light time can help to ease traffic pressure and save transportation *** this paper,Interval type-2 fuzzy sets and matched-degree are applied to the time of intersection signal adjusting,and five words are used to cover the range of adjusting lights’time,finally according to the average number of stranded vehicles,a query table is built to inquire and control the signal time during a certain period.

关键词： Interval type-2 fuzzy sets footprint of uncertainty computing with words traffic light time

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Leader-Following Output Consensus in a Network of Linear Agents with Communication Noises

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IFAC Proceedings Volumes 2014年第3期47卷 1825-1830页

作者： Yunpeng Wang Long Cheng Zeng-Guang Hou Min Tan Ming Wang State Key Laboratory of Management and Control for Complex Systems (SKLMCCS) Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Information and Electrical Engineering Shangdong Jianzhu University Jinan 250101 China

The leader-following output consensus problem of multi-agent systems (MAS) is studied in this paper. Each agent is modeled by a single-input single-output (SISO) system which can be further described by a controllable and observable linear state space model. An observer is constructed to estimate the agent's state, and the estimated state is shared with neighbor agents via the noisy communication channels. Similar to the previous work, in the proposed protocol a time-varying gain is employed to attenuate the noise's effect. However, in this paper, each agent is allowed to have its own time-varying gain. Some sufficient conditions on the time-varying gain are given for ensuring the consensus in the mean square sense. Finally, a simulation example is presented to verify the theoretical results.

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DCT representations based appearance model for visual tracking

DCT representations based appearance model for visual tracki...

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IEEE International Conference on Robotics and Biomimetics

作者： Hongkai Chen Weizheng Zhang Xiaoguang Zhao Min Tan State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China State Grid Henan Electric Power Company Zhengzhou China

ISBN: (纸本)9781479973989

In this paper, we present a simple yet effective visual tracking algorithm with an appearance model based on 2D discrete cosine transform (2D-DCT) representations. The DCT has the properties of decorrelation and energy compaction, and is robust against geometry and illumination changes. Hence, it is suitable for appearance modeling and the features of our appearance model are extracted from an optimized low dimensional subspace. In order to adapt to the appearance change caused by environment change or ego motion, we also propose to update the observation appearance model through a nonlinear weighted method. Numerous experiments on some challenging video sequences demonstrated that our algorithm is effective and it considerably outperforms the other methods.

关键词： Discrete cosine transforms Target tracking Visualization Adaptation models Lighting Robustness Feature extraction

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A Hierarchical Classification Algorithm for Evaluating Energy Consumption Behaviors

A Hierarchical Classification Algorithm for Evaluating Energ...

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International Joint Conference on Neural Networks

作者： Li Bu Dongbin Zhao Yu Liu Qiang Guan The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Institute of Automation Chinese Academy of Sciences Beijing Beijing CN

Researches on office building energy consumption have been hot in these years, but few researchers consider the classification of office energy consumption performance which can evaluate user behaviors in order to offer a clear analysis of energy consumption and improve their energy saving consciousness. In this paper, we propose a novel hierarchical classification algorithm for evaluating energy consumption behaviors at a real energy management system, which combines fuzzy c-means clustering with GA (genetic algorithm)-based SVM (support vector machine) to fully utilize collected samples. The experiment results with real energy consumption data show that the proposed algorithm works well to distinguish the abnormal behaviors and classify energy consumption behaviors accurately on normal offices.

关键词： Energy consumption Classification algorithms Support vector machines Buildings Training Clustering algorithms Labeling

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Interventions of traffic flow for Intersection Based on Interval type-2 fuzzy sets

Interventions of traffic flow for Intersection Based on Inte...

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2014 International Conference on Informative and Cybernetics for Computational Social systems(ICCSS2014)

作者： Xuan Li Hong Mo Feng Hua Zhu College Of Electrical And Information Engineering Changsha University Of Science And Technology State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

Assessment and analysis of the intersection status can help to make the right choice of interventions,it’s can bring convenience to solve the traffic *** this paper,interval type-2 fuzzy sets is applied in the analysis of the intersection state and congestion intervention,dynamic fuzzy comprehensive evaluation and footprint of uncertainty are used to assess the intersection *** with the example of intersection congestion,through corresponding intervention measures to improve the intersections crowded *** the linguistic dynamic orbits of road status figured out.

关键词： interval type-2 fuzzy sets footprint of uncertainty intervention measures linguistic dynamic orbits

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Research on Multi-Dimensional Data Visualization Analysis of Large Enterprise's Purchasing Fund

Research on Multi-Dimensional Data Visualization Analysis of...

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2014 IEEE International Conference on Service Operations and Logistics,and Informatics

作者： Minhui Lv Hongxia Zhao School of Management Huazhong University of Science and Technology Department of Equipment Economics and Management Naval University of Engineering The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

With the continuous development of data storage technology,the complexity,category and size of data increase sharply;on the other hand,the wide expansion of its application domain brings great challenges on the traditional data processing and analysis *** this paper,the data analysis and processing technology and its development status are introduced and by multi-dimensional data visualization analysis method and combining the knowledge of domain experts,the equipment purchasing fund data of a large enterprise is analyzed to provide reliable management decision to the investment and investment volume of business fund.

关键词： data analysis data mining visualization corporate purchasing fund

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