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Plant growth simulation algorithm for solving bilevel symbiosis optimization between manufacturing enterprise and logistics enterprise

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ICIC Express Letters 2014年第2期8卷 629-636页

作者： Li, Tong Jiang, Yufei Chen, Chouyong Ji, Tongcai Management College Hangzhou Dianzi University No. 2 St Hangzhou 310018 China Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University No. 10 Xuefu St. Jinzhou New District Dalian 116622 China

An intelligence optimization algorithm for solving nonlinear bilevel programming is proposed herein. In this algorithm, the upper solution space and lower reaction set of bilevel programming are looked as two growth environments of plants. Then the plant system evolution style based on growth regulation and the probability growth model based on plant phototropism theory are established. The optimization model combined with above two has realized the evolution of artificial plant from initial status to whole final status (that means no new branch growing), thus the optimal solutions of bilevel programming can be found. The algorithm herein shows its high accuracy and strong astringency. This article solves the problem of bilevel symbiosis optimization between manufacturing enterprise and logistics enterprise by using this algorithm, and the result shows that Plant Growth Simulation Algorithm (PGSA) has good effectiveness and feasibility. © 2014 ISSN 1881-803X.

关键词： Optimization

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Face recognition based on independent component analysis image reconstruction and linear discriminant analysis

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ICIC Express Letters 2014年第9期8卷 2457-2462页

作者： Zhou, Changjun Wang, Lan Lv, Ling Zheng, Xuedong Wei, Xiaopeng Zhang, Qiang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University No. 10 Xuefu Street Jinzhou Xinqu Dalian 116622 China Department of Mechanical Engineering Dalian Institute of Science and Technology No. 999-26 Bingang Road Lvshun District Dalian 116052 China

Independent Component Analysis (ICA) and Linear Discriminant Analysis (LDA) are two conventional methods in feature extraction. In this paper, we propose a novel face recognition method which is based on ICA image reconstruction, LDA and SVM. Firstly, we use the inner-classes covariance matrix as generating matrix, and then we can obtain eigenvectors from each person and the reconstructed images through ICA method. Secondly, the residual images are computed by subtracting reconstructed images from original face images. Furthermore, the residual images are applied by LDA to obtain the coefficient matrices. Finally, the features are utilized to train and test SVMs for face recognition. The experimental results on the ORL face database are presented to demonstrate the efficacy of the proposed method. © 2014 ISSN 1881-803X.

关键词： Image reconstruction

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Improved hybrid optimization algorithm for 3D protein structure prediction

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Journal of molecular modeling 2014年第7期20卷 2289页

作者： Changjun Zhou Caixia Hou Xiaopeng Wei Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Dalian University Dalian China

A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins.

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RGB Color Image Encryption Method Based on Lorenz Chaotic System and DNA Computation

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IETE technical review 2013年第5期30卷 404-409页

作者： Qiang Zhang Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing (Dalian University) Ministry of Education Dalian 116622 China

In this paper, an RGB color image encryption method based on the Lorenz chaotic system and DNA computation is presented. This method can not only change the location of the image pixel but also change the pixel values. Firstly, we split the RGB color image into R, G, B three components. Then, we use the 2D-hyperchaotic sequence to disorder the location of R, G, B three-component pixels. Secondly, three different chaotic sequences are generated by a one-dimensional logistic chaotic map, and the pixel values of the three components R, G, B can be scrambled through the three logistic chaotic sequences. Then the R, G, B digital images can be transformed into DNA coding matrices based on DNA coding rules. Thirdly, 3D chaotic sequences are generated by use of Lorenz chaotic system and are encoded based on DNA encoding rules in order to generate three DNA sequences. Finally, the encrypted image can be obtained by utilizing DNA operations on the DNA sequences of three components R, G, B and DNA sequences generated by the Lorenz chaotic system. The experiment results and encryption effect demonstrate that the proposed scheme is effective, and it has strong sensibility, high security, and good ability of resisting statistic attack.

关键词： 2D-hyperchaotic DNA computation Logistic chaotic map Security color image Security pixel DNA Computation cryptography Lorenz chaotic system DNA Sequence red-green-blue colour model

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A novel couple images encryption algorithm based on DNA subsequence operation and chaotic system

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Optik 2013年第23期124卷 6276-6281页

作者： Qiang Zhang Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing (Dalian University) Ministry of Education Dalian 116622 China

A novel couple images encryption algorithm based on DNA subsequence operation and chaotic system is presented. Different from the traditional DNA encryption methods, our algorithm is not use complex biological operation, but just uses the idea of DNA subsequence operation (such as elongation operation, truncation operation, and deletion operation). And then, do the DNA addition operation under the Chen's Hyper-chaotic map in this image cipher. The simulation experimental results and security analysis show that our algorithm not only has good encryption effect, but also has the ability of resisting exhaustive attack and statistical attack.

关键词： Image encryption DNA sequence Subsequence operation Addition operation Chen's hyper-chaotic Lorenz Security

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Face recognition based on PCA image reconstruction and LDA

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Optik 2013年第22期124卷 5599-5603页

作者： Changjun Zhou Lan Wang Qiang Zhang Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

Face recognition has become a research hotspot in the field of pattern recognition and artificial intelligence. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are two traditional methods in pattern recognition. In this paper, we propose a novel method based on PCA image reconstruction and LDA for face recognition. First, the inner-classes covariance matrix for feature extraction is used as generating matrix and then eigenvectors from each person is obtained, then we obtain the reconstructed images. Moreover, the residual images are computed by subtracting reconstructed images from original face images. Furthermore, the residual images are applied by LDA to obtain the coefficient matrices. Finally, the features are utilized to train and test SVMs for face recognition. The simulation experiments illustrate the effectivity of this method on the ORL face database.

关键词： PCA Image reconstruction Residual images LDA Face recognition

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Inferring gene regulatory network from bayesian network model based on re-sampling

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Telkomnika 2013年第1期11卷 215-222页

作者： Zhang, Qian Zheng, Xuedong Zhang, Qiang Zhou, Changjun Key Laboratory of Advanced Design and Intelligent Computing Dalian university Ministry of Education Dalian 116622 China

Nowadays, gene chip technology has rapidly produced a wealth of information about gene expression activities. But the time-series expression data present a phenomenon that the number of genes is in thousands and the number of experimental data is only a few dozen. For such cases, it is difficult to learn network structure from such data. And the result is not ideal. So it needs to take measures to expand the capacity of the sample. In this paper, the Block bootstrap re-sampling method is utilized to enlarge the small expression data. At the same time, we apply "K2+T" algorithm to Yeast cell cycle gene expression data. Seeing from the experimental results and comparing with the semi-fixed structure EM learning algorithm, our proposed method is successful in constructing gene networks that capture much more known relationships as well as several unknown relationships which are likely to be novel.

关键词： Gene expression

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Analysis on exponential stability of genetic regulatory networks with variable delays

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Journal of Computational and Theoretical Nanoscience 2013年第11期10卷 2604-2608页

作者： Zhang, Qiang Wei, Xiaopeng Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

This paper presents an analysis method to the global exponential stability for the delayed genetic regulatory networks with SUM regulatory functions. By transforming the kinetics of networks into a single delay differential equation and utilizing the method of delay differential inequalities, several sufficient conditions for ensuring global exponential stability of the genetic regulatory networks with variable delays are derived. Since our method does not make use of Lyapunov functionals, it is simpler and more straightforward. Two numerical examples are provided to show the validity of the obtained results. Copyright © 2013 American Scientific Publishers.

关键词： Differential equations

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A hybrid algorithm for protein structure prediction

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Journal of Computational and Theoretical Nanoscience 2013年第11期10卷 2701-2707页

作者： Zhou, Changjun Jiao, Yingying Zhang, Qiang Wang, Bin Wei, Xiaopeng Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian 116622 China

The prediction of protein structure that attracts many researchers to study is an NP-hard problem. In recent year, numerous algorithms are proposed. Although particle swarm optimizer has many advantages, the disadvantages of poor convergence precision and easy to trap into local optimum cannot be ignored. Tabu search which has been applied for various combination optimization problems is one of global optimization algorithms. So, in this paper, we put forward a hybrid algorithm of particle swarm optimizer (PSO) and tabu search (TS) for three-dimension protein structure prediction based on AB off-lattice protein model. Experiments show that the proposed algorithm performs better in predicting of protein structure. Copyright © 2013 American Scientific Publishers.

关键词： Tabu search

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A novel image fusion encryption algorithm based on DNA sequence operation and hyper-chaotic system

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Optik 2013年第18期124卷 3596-3600页

作者： Qiang Zhang Ling Guo Xiaopeng Wei Key Laboratory of Advanced Design and Intelligent Computing (Dalian University) Ministry of Education Dalian 116622 China

A new image fusion encryption algorithm based on image fusion and DNA sequence operation and hyper-chaotic system is presented. Firstly, two DNA sequences matrices are obtained by encoding the original image and the key image. Secondly, using the chaotic sequences generated by Chen's hyper-chaotic maps to scramble the locations of elements from the DNA sequence matrix which generated form original image. Thirdly, XOR the scrambled DNA matrix and the random DNA matrix by using DNA sequence addition operation. At last, decoding the DNA sequence matrix, we will get the encrypted image. The simulation experimental results and security analysis show that our algorithm not only has good encryption effect, but also has the ability of resisting exhaustive attack and statistical attack.

关键词： Image encryption DNA sequence XOR operation Chen's hyper-chaotic Security

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