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International Conference on Computational Intelligence and Security

作者： Guo Xie Minying Ye Xinhong Hei Jinwei Zhao Fucai Qian Xi'an University of Technology Xi'an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

Taking into account that the present popular methods, such as the judgement of the axle failure based on temperature threshold, and the early warning of axle based on real-time temperature analysis, cannot analyze the changing of performance trends, a health state analysis method for the axle of high-speed train based on long-term temperature monitoring data is proposed in this paper, which including the following main steps: (1) Preprocessing of the original data to correct the singular zero value and complement the missing values, (2) Smoothing of the processed data in order to automatically extract the beginning and end points of every temperature rising stage of axles, (3) Establishment of the calculation method of temperature rising rate, and evaluating the health sate of axles based on the temperature rising rate. Finally, the proposed method is validated based on the data from a test line, the results demonstrate the effectiveness and practicability of the method.

关键词： Axles Temperature distribution Aging Safety Data mining Fault diagnosis Monitoring

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Tissue P Systems with Look-ahead Mode

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Chinese Journal of Electronics 2014年第1期23卷 81-86页

作者： JIANG Yun SONG Tao ZHANG Zheng School of Computer Science and Information Engineering Chongqing Technology and Business University Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology

Tissue P systems are a class of distributed and parallel computing models inspired from inter-cellular communication and cooperation between cells. In this work, a variant of tissue P system, named tissue P system with look-ahead mode, is discussed for decreasing the inherent non-determinism of tissue P systems and helping implementing tissue P systems on computers. Such systems are proved to be universal by simulating register machine, and they are also proved to be able to efficiently solve computationally hard problems by means of a spacetime tradeoff, which is illustrated with a polynomial solution to 3-coloring problem.

关键词： Tissue P system Look-ahead mode Recursively enumerable language Cell separation 3-Coloring

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A New Logistic Map Based Chaotic Biogeography-based Optimization Approach for Cluster Analysis

A New Logistic Map Based Chaotic Biogeography-based Optimiza...

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2016 IEEE International Conference on Progress in Informatics and Computing

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang School of Computer Science and Technology Nanjing Normal University Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Department of Electrical Engineering The city college of New YorkCUNY Department of Mechanical and Control Engineering Kyushu Institute of Technology School of Information Engineering Yangzhou University School of Physics and Electronic Engineering Taizhou University School of Electronic Information Shanghai Dianji University School of Energy and Mechanical Engineering Nanjing Normal University Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization(CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： chaotic biogeography-based optimization cluster analysis centroid-based clustering simulation particle swarm optimization

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AN ADAPTIVE MEMBRANE ALGORITHM FOR SOLVING COMBINATORIAL OPTIMIZATION PROBLEMS

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Acta Mathematica Scientia 2014年第5期34卷 1377-1394页

作者：贺娟娟肖建华邵泽辉 Key Laboratory of Image Processing and Intelligent Control School of AutomationHuazhong University of Science and Technology The Research Center of Logistics Nankai University School of Information Science and Technology Chengdu University

Membrane algorithms （MAs）, which inherit from P systems, constitute a new parallel and distribute framework for approximate computation. In the paper, a membrane algorithm is proposed with the improvement that the involved parameters can be adaptively chosen. In the algorithm, some membranes can evolve dynamically during the computing process to specify the values of the requested parameters. The new algorithm is tested on a well-known combinatorial optimization problem, the travelling salesman problem. The em-pirical evidence suggests that the proposed approach is efficient and reliable when dealing with 11 benchmark instances, particularly obtaining the best of the known solutions in eight instances. Compared with the genetic algorithm, simulated annealing algorithm, neural net-work and a fine-tuned non-adaptive membrane algorithm, our algorithm performs better than them. In practice, to design the airline network that minimize the total routing cost on the CAB data with twenty-five US cities, we can quickly obtain high quality solutions using our algorithm.

关键词： membrane algorithm adaptation travelling salesman problem

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Blind source separation with evolution based KICA

Blind source separation with evolution based KICA

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Asia Pacific Conference on Multimedia and Broadcasting (APMediaCast)

作者： Peng Wu Qian Yin Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China Shandong Provincial Key Laboratory of Network based Intelligent Computing University of Jinan Jinan China

ISBN: (纸本)9781479979684

Kernel independent component analysis (KICA) has been widely used in the field of blind source separation. The selection of kernel function and its parameters plays an important role in KICA algorithm performance. An optimal kernel model should be rich enough to well map the given samples. However, users usually use a singular kernel based model in their experiments, which leads to a suboptimal kernel model. In order to solve this problem, we propose the evolution based multiple kernel independent component analysis (EMKICA), in which a convex combination of multiple base kernels is used instead of single kernel of KICA. The combination weights are learned by particle swarm optimization algorithm. Firstly, we elaborate the basic theory of KICA and concept of EMKICA, also the combination form of the composition kernel used in EMKICA. Secondly, we describe the presentation of the individuals in the particle swarm optimization algorithm, the settings of the evaluation function and general algorithm. Finally, we evaluate the separation ability of EMKICA on three different data sets including one-dimensional mixed signals, composite images and images with reflection. The experimental results verify the effectiveness of EMKICA.

关键词： Kernel Independent component analysis Algorithm design and analysis Multimedia communication Correlation Optimization Asia

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Cell resistance slope combined with LVQ neural network for prediction of anode effect

Cell resistance slope combined with LVQ neural network for p...

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International Conference on intelligent control and Information processing (ICICIP)

作者： Kaibo Zhou Zhikai Lin Dengzhi Yu Bin Cao Ziqian Wang Sihai Guo School of Automation Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Wuhan China Guiyang Aluminum Magnesium Design and Research Institute Guiyang China School of Automation Wuhan University of Technology Wuhan China

It is an important part in aluminum electrolysis production to control the anode effect (AE). Since there are some shortcomings in traditional methods of anode effect prediction in aluminum electrolysis, this paper combined two methods, the slope of cell resistance and learning vector quantization (LVQ) neural network, to predict anode effect. First of all, the first prediction of anode effect will be conducted based on the slope of cell resistance. Afterwards, the inaccurate data are supposed to be re-predicted. The second prediction consists of two steps, one is to estimate the power spectrum from the signal of cell resistance by means of periodogram, the other is to re-predict the anode effect with the LVQ neural network, since the energy of frequency bands are served as the input feature variables of neural network, so as to raise the accuracy of prediction. It turned out that the success rate of ten-minute in advance prediction for anode effect can be above 85%, though just cell resistance signal is studied.

关键词： Resistance Decision support systems Neural networks Spectral analysis Data acquisition Vector quantization

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Global coordinated tracking of multi-agent systems with disturbance uncertainties via bounded control inputs

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Nonlinear Dynamics 2015年第4期82卷 2059-2068页

作者： Su, Housheng Chen, Michael Z. Q. Wang, Xiaofan School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan China Department of Mechanical Engineering The University of Hong Kong Pokfulam Hong Kong Department of Automation Shanghai Jiao Tong University Shanghai China

This paper investigates the problem of global coordinated tracking of a multi-agent system with input additive uncertainties and disturbances via bounded control inputs. Scheduled low-and-high gain feedback-based distributed coordinated tracking protocols are developed. It is shown that, under the assumptions that each agent is asymptotically null controllable with bounded controls and the network is connected, global coordinated tracking of the multi-agent system can be achieved. We finally show some numerical simulations to verify and illustrate the theoretical results.

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Self-triggered Based Semi-global Consensus Tracking of Multi-agent Systems with Input Saturation

Self-triggered Based Semi-global Consensus Tracking of Multi...

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第三十四届中国控制会议

作者： Xiaoling Wang Housheng Su Jiwei Li Xiaofan Wang Department of Automation Shanghai Jiaotong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 P. R. China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 P. R. China

ISBN: (纸本)9781467374439

Self-triggered control is a technique which can determine the next sampling instant by virtue of the last sampling information. Combining this technique and the low-gain feedback one, we investigate the consensus tracking of general linear multi-agent systems with input saturation and updating delays in this paper. Specific formulations of heterogenous updating delays and heterogenous sampling periods are acquired to guarantee the semi-global consensus tracking of multi-agent systems. Numerical simulations are provided to verify the main results.

关键词： Multi-agent Systems Consensus Tracking Self-triggered Technique Input Saturation Low-gain Feedback Multi-agent systems sampling time tracking

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Portrait image segmentation based on improved grabcut algorithm 6th

Portrait image segmentation based on improved grabcut algori...

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6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015

作者： Li, Shuai Zheng, Xiaohui Chen, Xianjun Zhan, Yongsong Key Laboratory of Cloud Computing and Complex System Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Experiment Center of Information Science Guilin University of Electronic Technology Guilin Guangxi541004 China Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin Guangxi541004 China Information Engineering School Haikou College of Economics Haikou Hainan571127

ISBN: (纸本)9783319204680

Traditional computer portrait caricature system mainly take the method that exaggerate and deform real images directly, that lead the facial image background also been deformed when exaggerate facial image. If in pretreatment stage, we segmented the characters and background of the input image, and then do the subsequent processing, the problem may be solved. But for better portrait caricature effects, we need an excellent segmentation algorithm. So, we propose an improved Grabcut image segmentation algorithm and use it to extract the prospect character image for exaggeration and deformation. In practical application, we separate deform and exaggerate the foreground characters image with TPS method, then fuse it with the original or new background picture, get the final image. Application proves, the method solves the background deformation problem well, and improves the quality and rate of image segmentation, caricature synthesis effect reality and natural. © Springer International Publishing Switzerland 2015.

关键词： image segmentation

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Motion control and fall detection of intelligent cane robot

Springer Tracts in Advanced Robotics

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Springer Tracts in Advanced Robotics 2015年 106卷 317-337页

作者： Fukuda, Toshio Huang, Jian Di, Pei Sekiyama, Kosuge Key Laboratory of Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology No. 1037 Luoyu Road Wuhan Hubei430074 China Department of Micro-Nano Systems Engineering Nagoya University Furo-cho Chikusa-ku Nagoya464-8603 Japan

An intelligent cane robot was designed for aiding the elderly and handicapped people walking. The robot consists of a stick, a group of sensors and an omni-directional basis driven by three Swedish wheels. Multiple sensors were used to recognize the user’s "walking intention", which is quantitatively described by a new concept called intentional direction (ITD). Based on the guidance of filtered ITD, a novel intentionbased admittance motion control (IBAC) scheme was proposed for the cane robot. The experiment results demonstrated that the user feels more natural and comfortable when walking with the assistance of cane robot controlled by the IBAC strategy. To detect the fall of user, a detection method based on Dubois possibility theory was proposed using the combined sensor information from force sensors and a laser ranger finder (LRF) fixed on the cane robot. The human fall model was represented in a two-dimensional space, where the relative position between the Zero- Moment-Point (ZMP) and the center of support triangle was utilized as a significant feature. The effectiveness of proposed fall detection method was also confirmed by experiments. © Springer International Publishing Switzerland 2015.

关键词： Motion control

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