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Bacterial foraging algorithm based on quantum-behaved particle swarm optimization and opposition-based learning

Journal of Computational information Systems 2013年第3期9卷 1157-1165页

作者： Mai, Xiongfa Li, Ling Science Computing and Intelligent Information Processing of GuangXi Higher Education Key Laboratory Guangxi Teachers Education University Nanning 530023 China Ministry of Education Nanning 530001 China

Bacterial Foraging Optimization(BFA) algorithm has recently emerged as a very powerful technique for real parameter optimization, but the E. coli algorithm depends on random search directions which may lead to delay in reaching the global solution, while the reproduction step of BFA may reduce its diversity for in this step one better bacterium split into two same bacterium. In order to overcome the delay in optimization and to further enhance the performance of BFA, a bacterial foraging algorithm based on QPSO and OBL(OQ-BFA) is presented. The new algorithm is proposed to combine all algorithms' advantages in order to get better optimization values. Simulation results on eight benchmark functions show that the proposed algorithm is superior to the BFA, QPSO and BF-PSO. Copyright © 2013 Binary information Press.

关键词： Escherichia coli

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Journal of Multimedia 2013年第6期8卷 816-822页

作者： Sun, Shanhui Li, Zhuangzhuang Wu, Yimin Xu, Yan Laboratory of Intelligent Information Processing Suzhou University Anhui China College of Mathematics and Statistics Suzhou University Anhui China School of Computing National University of Singapore Singapore Singapore

The article mainly studies the contracting similarity fixed point and the structure of the general Sierpinski gasket. Firstly, the paper analyzes the importance of contracting similarity fixed point in fractal geometry. Based on a series of definitions, the article studies the contracting similarity fixed point. Then, the paper researches on the structure of the general Sierpinski gasket, and describes it through function. Using a new characteristic function and other techniques, the article gives two important lemmas of the general Sierpinski gasket and the complete proof. By the proved lemmas, the article gets the formula of the contracting similarity fixed point of the Sierpinski gasket, and then proves that the aforementioned contracting similarity fixed points form a new fractal. As application, the paper classifies the above contracting similarity fixed points into three types and gives two examples. © 2013 Academy Publisher.

关键词： Fractals

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Control of Hopf bifurcation in Internet congestion control model via time-delayed feedback control

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information Technology Journal 2013年第18期12卷 4493-4497页

作者： Xu, Xian-Fan Fan, Guo Ding, Da-Wei Yi, Liu Han, Liu-Jun School of Electronics and Information Engineering Anhui University 230601 Hefei China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University 230039 Hefei China

In this study, we are concerned with controlling Hopf bifurcation in a dual model of Internet congestion control algorithms. The stability of this system depends on a communication delay parameter, and Hopf bifurcation occurs when the communication delay passes through a critical value. Comparing with previous work, a time-delayed feedback method is proposed to postpone the onset of undesired Hopf bifurcation and improve stability of the dual model. Theoretical analysis and numerical simulation are provided to verify the effectiveness of our method. © 2013 Asian Network for Scientific information.

关键词： Hopf bifurcation

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2-D shape completion with shape priors

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Chinese Science Bulletin 2013年第27期58卷 3430-3436页

作者： GUO Ge JIANG TingTing WANG YiZhou GAO Wen Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences National Engineering Laboratory for Video Technology Key Laboratory of Machine Perception School of EECS Peking University

We propose new techniques for 2-D shape/contour completion, which is one of the important research topics related to shape analysis and computer vision, e.g. the detection of incomplete objects due to occlusion and noises. The purpose of shape completion is to find the optimal curve segments that fill the missing contour parts, so as to acquire the best estimation of the original complete object shapes. Unlike the previous work using local smoothness or minimum curvature priors, we solve the problem under a Bayesian formulation taking advantage of global shape prior knowledge. With the priors, our methods are expert in recovering significant shape structures and dealing with large occlusion cases. There are two different priors adopted in this paper: (i) A generic prior model that prefers minimal global shape transformation (including non-rigid deformation and affine transformation with respect to a reference object shape) of the recovered complete shape; and (ii) a class-specific shape prior model learned from training examples of an object category, which prefers the reconstructed shape to follow the learned shape variation models of the category. Efficient contour completion algorithms are suggested corresponding to the two types of priors. Our experimental results demonstrate the advantage of the proposed shape completion approaches compared to the existing techniques, especially for objects with complex structure under severe occlusion.

关键词：形状结构计算机视觉贝叶斯公式电子相关最佳估计最小曲率先验知识仿射变换

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Twin support vector machines based on Quantum particle swarm optimization

Journal of Software

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Journal of Software 2013年第7期8卷 1743-1750页

作者： Ding, Shifei Wu, Fulin Nie, Ru Yu, Junzhao Huang, Huajuan School of Computer Science and Technology China University of Mining and Technology Xuzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

Twin Support Vector Machines (TWSVM) are developed on the basis of Proximal Support Vector Machines (PSVM) and Proximal Support Vector Machine based on the generalized eigenvalues(GEPSVM). The solving of binary classification problem is converted to the solving of two smaller quadratic programming problems by TWSVM. And then it gets two non-parallel hyperplanes. Its efficiency of dealing with the problems and performance are better than the traditional support vector machines. However, it also has some problems. Its own parameters are difficult to be appointed. In order to solve this problem, on the basis of in-depth study of TWSVM, this paper proposes an algorithm that is the Twin Support Vector Machines based on Quantum Particle Swarm Optimization (QPSO-TWSVM).By the use of the global searching ability of the Quantum Particle Swarm Optimization (QPSO), QPSO-TWSVM can search the optimal parameters in the global scope and avoid itself falling into the local optimum prematurely to find the values of the parameters which are the closest to the optimal parameters. QPSO-TWSVM avoids using the empirical values to appoint the parameters successfully. Compared with the traditional TWSVM, QPSO-TWSVM can appoint the parameters more accurately and avoid selecting the parameters blindly. Because of the better parameter selections, QPSO-TWSVM improves the classification accuracy of TWSVM. © 2013 ACADEMY PUBLISHER.

关键词： Support vector machines

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Application of matlab/simulink in teaching course of communication principle

Application of matlab/simulink in teaching course of communi...

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2013 International Conference on Advanced information Engineering and Education Science, ICAIEES 2013

作者： Chang, Jing Li, Xiaohui Key Laboratory of Intelligent Computing and Singnal Processing School of Electronic Information Engineering Anhui University Anhui Province China

ISBN: (纸本)9789078677949

This paper applies Matlab software as an auxiliary method in teaching course of communication principle. Considering variety of abstract concepts in this course, such as digital modulation and demodulation, channel-coding, random signal analysis, we select Matlab aid to provide dynamical simulation for communication theory. This method is used both in class presentation and laboratory experiments, which is helpful for students to understand the theory knowledge, enhancing their practical skills. Moreover, it can also extend students' ability of programming. Compared to traditional teaching method, the teacher's interpretation written on blackboard is the main means, this method enables students to study actively and cultivate their scientific qualities. © 2013. The authors - Published by Atlantis Press..

关键词： Simulink

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A feature weighted spectral clustering algorithm based on knowledge entropy

Journal of Software

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Journal of Software 2013年第5期8卷 1101-1108页

作者： Jia, Hongjie Ding, Shifei Zhu, Hong Wu, Fulin Bao, Lina School of Computer Science and Technology China University of Mining and Technology Xuzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

Spectral clustering has aroused extensive attention in recent years. It performs well for the data with arbitrary shape and can converge to global optimum. But traditional spectral clustering algorithms set the importance of all attributes to 1 as default, when measuring the similarity of data points. In fact, each attribute contains different information and their contributions to the clustering are also different. In order to make full use of the information contained in each attribute and weaken the interference of noise data or redundant attributes, this paper proposes a feature weighted spectral clustering algorithm based on knowledge entropy (FWKE-SC). This algorithm uses the concept of knowledge entropy in rough set to evaluate the importance of each attribute, which can be used as the attribute weights, and then applies spectral clustering method to cluster the data points. Experiments show that FWKE-SC algorithm deals with high-dimensional data very well and has better robustness and generalization ability. © 2013 ACADEMY PUBLISHER.

关键词： Entropy

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Fractal and multifractal properties of a family of fractal networks

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Journal of Statistical Mechanics: Theory and Experiment 2014年第2期2014卷 P02020-P02020页

作者： Li, Bao-Gen Yu, Zu-Guo Zhou, Yu Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan HUNAN 411105 China School of Mathematical Sciences Queensland University of Technology Brisbane GPO Box 2434 Q4001 Australia

In this work, we study the fractal and multifractal properties of a family of fractal networks introduced by Gallos et al (2007 Proc. Nat. Acad. Sci. USA 104 7746). In this fractal network model, there is a parameter e which is between 0 and 1, and allows for tuning the level of fractality in the network. Here we examine the multifractal behavior of these networks, the dependence relationship of the fractal dimension and the multifractal parameters on parameter e. First, we find that the empirical fractal dimensions of these networks obtained by our program coincide with the theoretical formula given by Song et al (2006 Nature Phys. 2 275). Then from the shape of the τ(q) and D(q) curves, we find the existence of multifractality in these networks. Last, we find that there exists a linear relationship between the average information dimension D(1) and the parameter e. © 2014 IOP Publishing Ltd and SISSA Medialab srl.

关键词： network dynamics networks random graphs

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Discovering the multi-neuronal firing patterns based on a new binless spike trains measure

Discovering the multi-neuronal firing patterns based on a ne...

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10th International Symposium on Neural Networks, ISNN 2013

作者： Lu, Hu Wei, Hui Laboratory of Cognitive Model Algorithm School of Computer Science Fudan University Shanghai 200433 China Shanghai Key Laboratory of Intelligent Information Processing Shanghai 200433 China

ISBN: (纸本)9783642390647

In this paper, we proposed a method which presented a new definition of different multi-step interval ISI-distance distribution of single neuronal spike trains and formed a new feature vector to represent the original spike trains. It is a binless spike train's measure method. We used spectral clustering algorithm on new multi-dimensional feature vectors to detect the multiple neuronal firing patterns. We tested this method on standard data set in machine learning, neuronal surrogate data set and in vivo multi-electrode recordings respectively. Results shown that the method proposed in this paper can effectively improve the clustering accuracy in standard data set and detect the firing patterns in neuronal spike trains. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Clustering algorithms

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Fractal and complex network analyses of protein molecular dynamics

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Physica A: Statistical Mechanics and its Applications 2014年 416卷 21-32页

作者： Yuan-Wu Zhou Jin-Long Liu Zu-Guo Yu Zhi-Qin Zhao Vo Anh Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan 411105 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China Civil Construction Engineering Department Guangxi University of Science and Technology Liuzhou 545006 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia

Based on protein molecular dynamics, we investigate the fractal properties of energy, pressure and volume time series using the multifractal detrended fluctuation analysis (MF-DFA) and the topological and fractal properties of their converted horizontal visibility graphs (HVGs). The energy parameters of protein dynamics we considered are bonded potential, angle potential, dihedral potential, improper potential, kinetic energy, Van der Waals potential, electrostatic potential, total energy and potential energy. The shape of the h ( q ) curves from MF-DFA indicates that these time series are multifractal. The numerical values of the exponent h ( 2 ) of MF-DFA show that the series of total energy and potential energy are non-stationary and anti-persistent; the other time series are stationary and persistent apart from series of pressure (with H ≈ 0.5 indicating the absence of long-range correlation). The degree distributions of their converted HVGs show that these networks are exponential. The results of fractal analysis show that fractality exists in these converted HVGs. For each energy, pressure or volume parameter, it is found that the values of h ( 2 ) of MF-DFA on the time series, exponent λ of the exponential degree distribution and fractal dimension d B of their converted HVGs do not change much for different proteins (indicating some universality). We also found that after taking average over all proteins, there is a linear relationship between 〈 h ( 2 ) 〉 (from MF-DFA on time series) and 〈 d B 〉 of the converted HVGs for different energy, pressure and volume.

关键词： Protein molecular dynamics Multifractal detrended fluctuation analysis Horizontal visibility graph Fractal analysis Degree distribution

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