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第35届中国控制会议

作者： WANG Duo PENG Zhihong School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology

ISBN: (纸本)9781509009107

In this paper we formulate and solve a pursuit-evasion game in which a single faster player chases several evaders with the same properties. We analyze the optimal motion strategies of the both sides by using the theory of differential games, which helps simplify computation complexity and meet an ideal result. We discuss the situation of one faster pursuer and one evader under some basic assumptions in which the amount of evaders increases by steps in the full visibility case. We apply the task allocation method to simulate the optimal motion track in both fixed sequence capture mode and free sequence capture mode of the pursuer. The optimal motion strategies acquired by differential games theory respond faster than those acquired in traditional ways. We prove all the chase process discussed with differential games by MATLAB simulation.

关键词： differential games pursuit-evasion game optimal strategy capture sequence

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Proposal of Initiative Service Model for Service Robot

Proposal of Initiative Service Model for Service Robot

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第十二届中国智能机器人大会

作者： Man Hao Weihua Cao Min Wu Zhentao Liu Luefeng Chen Ri Zhang School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Service robots are becoming a part of our *** realize friendly human-robot interaction,an initiative service model for service robot is proposed,which is composed of three layers,i.e.,information acquisition layer,in which communication information and environmental information are collected by sensors;decision layer,in which personal intention and emotional states are obtained by multi-modal emotion recognition and intention understanding,and users' demands are obtained by demand analysis model;initiative service execution layer,in which the task execution and emotion adaption of robot are carried *** service can sense motive of people,by which a humanized and real-time service could be *** service experiments are performed,including passive service and initiative service of *** results show that the drinking time of passive service lags behind the initiative service 30 minutes on average,and the initiative service renders drinking service 2 times more than passive service on average,besides,the water quantity provided by initiative service is more reasonable,which demonstrates the feasibility of the *** prospect,initiative service model could be applied to many occasions in our daily life,e.g.,family service,caring for the elderly,and medical rehabilitation.

关键词： service robots service pattern fuzzy production rules emotion recognition intention understanding

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Hybrid Prediction Model of Carbon Efficiency for Sintering Process

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IFAC-PapersOnLine 2017年第1期50卷 10238-10243页

作者： Hu J. Wu M. Chen X. She J. Cao W. Chen L. Ding H. School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China School of Engineering Tokyo University of Technology Hachioji Tokyo 192-0982 Japan School of Mechanical Engineering & Electronic Information China University of Geosciences Wuhan 430074 China

Sintering process is the second most energy-consuming process in ironmarking. The main source of energy consumption is the consumption of carbon. It is significant to predict the carbon efficiency to reduce the energy consumption. In the paper, first, the comprehensive coke ratio (CCR) is defined and used as an index to measure the carbon efficiency by analyzing the sintering mechanism. The principal component analysis method is used to find the principal components affecting the CCR. Next, they are divided into different subclasses by adopting the fuzzy C-means clustering algorithm. Then, the least square-support vector machine (LS-SVM) sub-models are established based on the subclasses, and the parameters of the sub-models are obtained using an adaptive particle swarm optimization algorithm. Finally, a FCM-LSSVM model is established by weighting each LS-SVM sub-model with a fuzzy membership function. The simulations using actual production data show that the prediction accuracy of the FCM-LSSVM model is higher than that of a BP neural network model and a single LS-SVM model, and it meets the requirements of actual production. © 2017

关键词： Adaptive particle swarm optimization Comprehensive coke ratio Fuzzy C-means LS-SVM model Principal component analysis Sintering process

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A four-stage localization method for epileptic seizure onset zones

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IFAC-PapersOnLine 2017年第1期50卷 4412-4417页

作者： Wan T. Wu M. Lai X. Wan X. She J. Du Y. School of Automation China University of Geosciences Wuhan Hubei 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei 430074 China School of Engineering Tokyo University of Technology Hachioji Tokyo 192-0982 Japan School of Automation Guangdong University of Technology Guangzhou Guangdong 510006 China

This paper presents a four-stage localization method for epileptic seizure onset zones (SOZs). This method combines the advantages of both the Shannon-entropy-based complex Morlet wavelet transform (SE-CMWT) and adaptive-genetic-algorithm-based matching pursuit (AGA-MP) methods to achieve satisfactory localization performance. The Hilbert transform method is used to identify events of interest. The SE-CMWT-based power spectral density method is applied to acquire channels of interest (CoIs). By using the Morlet wavelets as the dictionary elements, the AGA-MP method combined with Morlet wavelets is developed to detect high-frequency oscillations (HFOs) on CoIs with faster speed and higher accuracy than the AGA-MP method. And the characteristics of HFOs are used to localize SOZs based on the half-maximum method. A comparison shows that our method has higher sensitivity and specificity than four existing methods. © 2017

关键词： Epilepsy Four-stage localization method High-frequency oscillation (HFO) Seizure onset zone (SOZ)

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Design of Low-cost Position Differential Positioning System Based on STM32

Design of Low-cost Position Differential Positioning System ...

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Chinese Automation Congress

作者： Haijun Fu Ming Qiu Xisong Dong Gang Xiong Haonan Xiong Xiang Su Shichao Chen Zhen Shen Xiujiang Guo School of Artificial Intelligence Beijing Union University Beijing China The Cloud Computing Center Chinese Academy of Sciences Dongguan China The Qingdao Academy of Intelligent Industries Macau University of Science and Technology Qingdao China Beijing Union University Beijing China School of Electrical Engineering and Electronic Information Xihua University Chengdu China The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China Department of Computer Science University of Helsinki Fin Finland Measurement Center Station PetroChina Huabei Oilfield Company Renqiu China

There exist some obstacles to realize high-precision positioning with using the position differential technique due to the limiting factors. However, with the advancement of chip performance and the establishment of multiple satellite navigation systems, position differential positioning can be realized to meet the civilian high-precision positioning demand while significantly reducing costs. This paper is to explore the engineering application and propose a new method. Through the experiments and data analysis, we have found the error correlation between two receivers in a small area and designed a set of positioning system, and programmed in the Keil μVision5 in C language. The system consists of the current mainstream low-cost STM32, UBLOX NEO 6M chip, NRF24L01 chip, GPS antenna and power supply module. Each two receivers can form a differential positioning system. At present, the system in the low-speed status is, in the urban environment, basically reaching within 0.5 - 3 m of the positioning error.

关键词： Position differential positioning Low cost Error correlation GPS STM32

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A novel fault diagnostic technique for photovoltaic systems based on cascaded forest 1

A novel fault diagnostic technique for photovoltaic systems ...

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1st Workshop on Smart Internet of Things, SmartIoT 2017

作者： Hu, Liangqing Ye, Jin Chang, Shengqiang Li, Hongtao Chen, Hongyu School of Computer Electronicsand Information Guangxi University Nanning China Innovation Center of Cloud Computing and Big Data Guilin University of Electronic Technology Guangxi Colleges and Universities Guilin China Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin China Shijiazhuang Kelin Electric Co. Ltd. Shijiazhuang China

ISBN: (纸本)9781450355285

A variety of faults often occurduring the operation of PV arrays, which may seriously affect the normal operation of the system, the machine diagnosis of the types of fault has become a hotspot in the field of photovoltaic power generation. This paper proposes a novel fault diagnostic technique for photovoltaic systems based on Cascaded Forest. Through the in-depth analysis of the output of PV arrays froma data platform of ShijiazhuangKelin Electric Co, the input variables of the diagnosis model are obtained. Compared with other fault diagnosis methods for the PV array, the proposed method can work under a small number of tagged data and the system can be run online and real-time. Finally, the experimental results show that the fault diagnosis method for the PV array based on the cascading forests can effectively detect four types of fault for PV array such as short-circuit, open-circuit, abnormal degradation and partial shading. This method has a good value for the intelligent fault diagnosis of PV. © 2017 Association for computing Machinery.

关键词： Information management

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Spike-burst chimera states in an adaptive exponential integrate-and-fire neuronal network

arXiv

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arXiv 2019年

作者： Santos, Moises S. Protachevicz, Paulo R. Iarosz, Kelly C. Caldas, Iberê L. Viana, Ricardo L. Borges, Fernando S. Ren, Hai-Peng Szezech, José D. Batista, Antonio M. Grebogi, Celso Department of Physics Federal University of Paraná CuritibaPR80060-000 Brazil Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology Xi'an710048 China Xian Technological University Xi'an710021 China Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute for Complex Systems and Mathematical Biology King's College University of Aberdeen AberdeenAB24 3UE United Kingdom

Chimera states are spatiotemporal patterns in which coherence and incoherence coexist. We observe the coexistence of synchronous (coherent) and desynchronous (incoherent) domains in a neuronal network. The network is composed of coupled adaptive exponential integrate-and-fire neurons that are connected by means of chemical synapses. In our neuronal network, the chimera states exhibit spatial structures both with spikes and bursts activities. Furthermore, those desynchronised domains not only have either spike or burst activity, but we show that the structures switch between spikes and bursts as the time evolves. Moreover, we verify the existence of multicluster chimera states. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

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FCM-based multiple random forest for speech emotion recognition 5

FCM-based multiple random forest for speech emotion recognit...

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5th International Workshop on Advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Zhou, Mengtian Chen, Luefeng Xu, Jianping Cheng, Xianghui Wu, Min Cao, Weihua She, Jinhua Hirota, Kaoru School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Engineering Tokyo University of Technology Tokyo192-0982 Japan Tokyo Institute of Technology Yokohama226-8502 Japan

Speech emotion recognition (SER) is of great importance in the human-robot interaction, and SER have been developed rapidly in recent years. How to identify high correlation features is a main question. In this paper, multiple random forest (MRF) is proposed, which can effectively predict up to several thousand explanatory variables, and improve the recognition result. At the mean time, personalized features and non-personalized features are fused for SER that can be divided into different subclasses by adopting the fuzzy C-means (FCM) clustering algorithm, then FCM-based MRF is proposed. Finally, our model is established, and the confusion matrix is output. Moreover, we conduct a separate classification of some certain emotion, which are difficult to recognition to some extent. And results show that the proposed method of FCM-based MRF achieves good performance for SER, which the recognition accuracy is 84.17%.

关键词： Clustering algorithms

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Compressive phase retrieval via reweighted amplitude flow

arXiv

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arXiv 2017年

作者： Zhang, Liang Wang, Gang Giannakis, Georgios B. Chen, Jie Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

The problem of reconstructing a sparse signal vector from magnitude-only measurements (a.k.a., compressive phase retrieval), emerges naturally in diverse applications, but it is NP-hard in general. Building on recent advances in nonconvex optimization, this paper puts forth a new algorithm that is termed compressive reweighted amplitude flow and abbreviated as CRAF, for compressive phase retrieval. Specifically, CRAF operates in two stages. The first stage seeks a sparse initial guess via a new spectral procedure. In the second stage, CRAF implements a few hard thresholding based iterations using reweighted gradients. When there are sufficient measurements, CRAF provably recovers the underlying signal vector exactly with high probability under suitable conditions. Moreover, its sample complexity coincides with that of the state-of-the-art procedures. Finally, substantial simulated tests showcase remarkable performance of the new spectral initialization, as well as improved exact recovery relative to competing alternatives. Copyright © 2017, The Authors. All rights reserved.

关键词： Iterative methods

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Detection of Android Malware Security on System Calls

Detection of Android Malware Security on System Calls

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2016 IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference(IMCEC 2016)

作者： Chen Da Zhang Hongmei Zhang Xiangli Guangxi Colleges and Universities Key Laboratory of cloud computing and complex systems Guilin University of Electronic Technology

ISBN: (纸本)9781509001668

In order to detect the security of Android software which isn't installed efficiently and accurately,this paper pro poses a new malware detection method based on system calls *** samples are pretreated by Classification to refine and distinguish characteristics of various types of Android software;Restrictions and normalization are applied to process system call frequency information to improve the detection *** with the characteristics of random forest algorithms and data obtained,optimal training model is set up,and ultimately Android software security is detected *** experiments,the detection accuracy rate of Android tool software and financial software more than 93 percent,with higher accuracy.

关键词： system calls android system malware detection classification algorithm

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