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A method of COA based on multi-agent evolutionary algorithm

A method of COA based on multi-agent evolutionary algorithm

引用

MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Yu, Xin Wang, Hui Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

Planning detailed military course of action (COA) is very complex and time consuming. In this paper, a method based on multi-agent evolutionary algorithm was presented to solve COA' resource management and scheduling problems. Each individual can be seen as an agent, in order to realize the local perceptivity of agents, the environment is organized as a latticelike structure. Each agent is fixed on a lattice point and it can only interact with its *** agent behaviors which are competition behavior and self-learning behavior are designed. In this work, constraint functions are considered as functions to be optimized like the objectives and then added in competition strategy to deal with the multi-objective aspect of resource-constrained project scheduling problems. This approach avoids the use of a penalty function to deal with constraints. At the same time, the added constraint functions could make the whole algorithm evolving feasible. The simulation results demonstrated that this approach could improve searching ability of this algorithm, and the precision of this method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Evolutionary algorithms

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An improved contour detection method based on level set and watershed transform

An improved contour detection method based on level set and ...

引用

MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Wang, Shuang Fu, Shenggao Jiao, Licheng Zhang, Xiaojing Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

In this paper, an improved contour detection method based on level set and watershed transform is proposed. It is performed on coarse-to-fine approach: 1) primary contours detected by using level set evolution;2) accurate contours detected by watershed transform. The combined method utilizes the advantages of level set method and watershed transform. Experimental results show that our method could detect accurate contours and gain great improvement compared with level set evolution and watershed transform. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Numerical methods

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Detecting flood change with multitemporal SAR images based on difference images fusion and fuzzy degree of nearness

Detecting flood change with multitemporal SAR images based o...

引用

MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Li, Jinji Jiao, Licheng Zhang, Xiangrrong Hou, Biao Yang, Dongdong Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

In this paper, we present a novel approach for detecting the changed regions caused by flooding events in multi-temporal SAR images. And the proposed method concludes two parts: 1) constructing difference image (DI) by fusion strategy proposed in this paper;2) producing change-detection map based on FCM and fuzzy degree of nearness. Experimental comparisons on real multi-temporal SAR images indicate that the proposed method can reduce the affection by speckle noise. Meanwhile, the proposed method can accurately detect the interested changed regions. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Synthetic aperture radar

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Improvement of Bandelets in cost function and coding strategy for SAR image compression

Improvement of Bandelets in cost function and coding strateg...

引用

2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Yang, Shuyuan Wu, Ruixia Meng, Huixiao Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424427314

Synthetic aperture radar (SAR) data collections can cover large areas at high resolution, generating massive amounts of data. Many existed transform-based compression techniques can effectively reduce the costs of storage and transmission with slight loss of information. As a new developed multi-resolution geometry analysis tool, Bandelet can make full use of intrinsic geometry regularity of images and exhibit enormous potential in image compression. In this paper, we propose a low complexity Bandelet transform for SAR image compression. A new cost function is defined to determine the optimal geometric flows in each dyadic squared sub-block of images, and an optimization of low frequency component followed by EBCOT coding of the Bandelet coefficients are employed. Some experiments are taken on some Ku-band SAR images came from Sandia National Laboratories and the results show the superiority of our proposed method over JPEG2000 and the second generation Bandelet in PSNR, ENL and EPI. ©2009 IEEE.

关键词： Cost functions

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Gene transposon based clonal selection algorithm for clustering

Gene transposon based clonal selection algorithm for cluster...

引用

11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009

作者： Liu, Ruochen Sheng, Zhengchun Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781605583259

Inspired by the principle of gene transposon proposed by Barbara McClintock, a new immune computing algorithm for clustering multi-class data sets named as Gene Transposition based Clone Selection Algorithm (GTCSA) is proposed in this paper, The proposed algorithm does not require a prior knowledge of the numbers of clustering;an improved variant of the clonal selection algorithm has been used to determine the number of clusters as well as to refine the cluster center. a novel operator called antibody transposon is introduced to the framework of clonal selection algorithm which can realize to find the optimal number of cluster automatically. The proposed method has been extensively compared with Variable-string-length Genetic Algorithm(VGA)based clustering techniques over a test suit of several real life data sets and synthetic data sets. The results of experiments indicate the superiority of the GTCSA over VGA on stability and convergence rate, when clustering multi-class data sets. Copyright 2009 ACM.

关键词： Genes

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Quantum-inspired evolutionary clustering algorithm based on manifold distance 09

Quantum-inspired evolutionary clustering algorithm based on ...

引用

2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC'09

作者： Yangyang, Li Hongzhu, Shi Maoguo, Gong Ronghua, Shang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781605583266

Based on the concepts and principles of quantum computing, a quantum-inspired evolutionary algorithm for data clustering (QECA) is proposed in this paper. And a novel distance measurement index called manifold distance is introduced. These attribute data are the main source of clustering problem, due to its complex distribution, most clustering algorithms available are only suitable for these types of characteristic data. In this study, a new algorithm which can deal with these data with manifold distribution is more effective. The main motives of using QECA consist in searching for appropriate cluster center so that a similarity metric of clusters are optimized more quickly and effectively. The superiority of QECA over fuzzy c-means (FCM) algorithm and immune evolutionary clustering algorithm (IECA) is extensively demonstrated in our experiments. Copyright 2009 ACM.

关键词： Clustering algorithms

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Synthetic aperture radar automatic target recognition based on curvelet transform

Synthetic aperture radar automatic target recognition based ...

引用

MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Wang, Shuang Liu, Zhuo Jiao, Licheng He, Jun Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

A novel synthetic aperture radar (SAR) automatic target recognition (ATR) approach based on Curvelet Transform is proposed. However, the existing approaches can not extract the more effective feature. In this paper, our method is concentrated on a new effective representation of the moving and stationary target acquisition and recognition (MSTAR) database to obtain a more accurate target region and reduce feature dimension. Firstly, MSTAR database can be extracted feature through the optimal sparse representation by curvelets to obtain a clear target region. However, considering the loss of part of edges of image. We extract coarse feature, which is to compensate fine feature error brought by segmentation. The final features consisting of fine and coarse feature are classified by SVM with Gaussian radial basis function (RBF) kernel. The experiments show that our proposed algorithm can achieve a better correct classification rate. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Automatic target recognition

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Simulated annealing and crowd dynamics approaches for intelligent control 6

引用

6th International Symposium of Neural Networks, ISNN 2009

作者： Zhang, Qingpeng Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology WuhanHubei430074 China

ISBN: (纸本)9783642012150

This is a survey of two approaches to intelligent control. The approaches are based on the author’s previous and ongoing projects in the Maximum Clique Problem (MCP) and the Crowd Dynamics. The ideas came from computational intelligence and fluid dynamics. One is Simulated Annealing (SA) algorithm and TABU search’s applications in the combinatorial search of intelligent control. Another one is from Continuum Dynamics and this approach can achieve a kind of group intelligence. This article is originally produced as a proposal and then a survey, thus is incomplete and lacking of simulation data. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Simulated annealing

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SAR target recognition based on improved sparse LSSVM

SAR target recognition based on improved sparse LSSVM

引用

MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Zhang, Xiangrong Zhang, Yifan Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478061

An Improved Fast Sparse Least Squares Support Vector Machine (IFSLSSVM) is proposed for Synthetic Aperture Radar (SAR) target recognition. Least Squares Support Vector Machine (LSSVM) is a least square version of Support Vector Machine (SVM), but it lacks the sparseness compared with SVM. IFSLSSVM, which combines the incremental learning and decremental learning, selects those important samples as the support vectors, and implements pruning by a certain condition, can solve the non-sparse problem of LSSVM effectively. Benchmarking UCI datasets are firstly used for testing the performance of our algorithm, followed by SAR target recognition. Experimental results on MSTAR SAR dataset show that IFSLSSVM is an effective SAR target recognition approach (SAR-ATR), which not only reduces the number of support vectors but also enhances the recognition rate. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Support vector machines

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A parallel artificial immune model for optimization

A parallel artificial immune model for optimization

引用

2009 International Conference on Computational Intelligence and Security, CIS 2009

作者： Qi, Yutao Liu, Fang Jiao, Licheng School of Computer Science and Technology Key Laboratory of Intelligent Perception and Image Xidian University Xi'an China Inst. of Intelligent Information Processing and Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China

ISBN: (纸本)9780769539317

This paper presents a parallel artificial immune model termed as tower master-slave model (TMSM) for solving optimising problems. Based on TMSM, the parallel immune memory clonal selection algorithm (PIMCSA) is also proposed. TMSM is a two level coarse-grained parallel artificial immune model with distributed immune response and distributed immune memory. In PIMCSA, vaccines are extracted and migrated between populations rather than individual migration as has been done in parallel genetic algorithms. It is a good balance between population diversity and the convergent speed. Experimental results on the numerical optimization and TSP problems show that PIMCSA achieves good performance in terms of both solution quality and computation time. © 2009 IEEE.

关键词： Genetic algorithms

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