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International Conference on Machine Vision and Human-Machine Interface (MVHI)

作者： Ye Tian Dayou Liu Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Jilin University Changchun Jilin CN

Particle swarm optimization (PSO) algorithm is a robust and efficient approach for solving complex real-world problems. In this paper, a modified particle swarm algorithm (IMPSO) is introduced for unconstrained global optimization. The whole swarm is partitioned to three different sub-populations according to their fitness, and different velocity updating strategies are used to different sub-populations. Besides, we take advantage of crossover to maintain the diversity of the swarm and avoid getting into local optimum. IMPSO are extensively compared with other two modified PSO algorithms on three well-known benchmark functions with different dimensions. Experimental results show that IMPSO achieves not only better solutions but also faster convergence.

关键词： Particle swarm optimization Partitioning algorithms educational institutions Marine animals Birds Testing Machine vision Man machine systems Computer science Laboratories

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A modal representation of RCC62

A modal representation of RCC62

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International Conference on Computer Sciences and Convergence Information Technology (ICCIT)

作者： Qian Fu Ji-hong Ouyang Da-you Liu Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Jilin University Changchun Jilin CN

The major problem in developing a useful formalism for reasoning about spatial information is the trade off between expressive power and computational tractability. Based on Bennett's modal representation of convex-hull and the RCC62 model which describes the topological relation between simple concave regions, the modal representation of RCC62 is presented in this paper, which has a theoretical advantage over 1st-order representations.

关键词： Cognition Calculus computational modeling Encoding knowledge engineering Laboratories

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A Novel Approach for Modeling Direction Relations Between Uncertain Regions

A Novel Approach for Modeling Direction Relations Between Un...

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International Conference on Machine Vision and Human-Machine Interface (MVHI)

作者： Yiqun Dong Dayou Liu Fang Wang Ye Tian Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Jilin University Changchun Jilin CN

Conventional models based on crisp regions can not deal with the Direction Relations between Uncertain Regions (DRUR). Using broad boundary to represent the uncertain boundary, a novel approach is proposed based on model SK for modeling DRUR in this paper. DRUR are described as the combinations of basic cardinal direction relations, then we study the composition of DRUR, and a method is put forward for calculating this composition.

关键词： Uncertainty Tiles Machine vision Man machine systems educational institutions Computer science educational technology Laboratories Computer interfaces Computer vision

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Solving SAT Problem with a Revised Hitting Set Algorithm

Solving SAT Problem with a Revised Hitting Set Algorithm

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The 2010 2nd International Conference on Future Computer and Communication(第二届未来计算机与通信国际会议 ICFCC 2010)

作者： Youjun Xu Dantong Ouyang Yuxin Ye Jialiang He College of Computer Science and Technology Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun China

ISBN: (纸本)9781424458219;9781424458240

The satisfiability(SAT) problem is a core problem of artificial intelligence. Research findings in SAT are widely used in many areas. The main methods solving SAT problem are resolution principle, tableau calculus and extension rule. Besides methods mentioned above, we find that the SAT problem can be solved with hitting set algorithms. If a set of clause is satisfiable, there must be a hitting set of the clause set which containing no complementary pairs of literals. Algorithm NEYVHS-tree is an efficient hitting set algorithm proposed by Ouyang. RNHST proposed in this paper is a revised algorithm in respect of ***-tree. It judges the satisfiability of a clause set by confirming the existence of the set's hitting set without complementary pairs of literals. The test result shows that RNHST is an efficient algorithm.

关键词： satisfiability problem hitting set minimal hitting set extension rule NEWHS-tree

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A self-adaptive differential evolution algorithm for binary CSPs

A self-adaptive differential evolution algorithm for binary ...

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International Conference on Natural computation

作者： Fu, Hongjie Ouyang, Dantong Xu, Jiaming Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China College of Computer Science and Technology Jilin University Changchun China College of Computer Science and Technology Jilin Teachers Institute of Engineering and Technology Changchun China College of Software Northeast Normal University Changchun China

ISBN: (纸本)9781424459612

A novel self-adaptive differential evolution (SADE) algorithm is proposed in this paper. SADE adjusts the mutation rate F and the crossover rate CR adaptively, taking account of the different distribution of population. In order to balance of an individual's exploration and exploitation capability for different evolving phase, F and CR equal to two different self-adjusted nonlinear functions. F and CR vary dynamically with each generation evolution. SADE maintains the diversity of population and improves the global convergence ability. It also improves the efficiency and success rate and avoids the premature convergence. Simulation and comparisons based on test-sets of CSPs demonstrate the effectiveness, efficiency and robustness of the proposed algorithm. © 2010 IEEE.

关键词： Efficiency

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An efficient and effective automatic image annotation using positive and negative example images

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ICIC Express Letters 2011年第8 B期5卷 2927-2932页

作者： Song, Haiyu Li, Xiongfei Wang, Pengjie Bao, Cuizhu Dong, Yuying Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University No. 2699 Qianjin Avenue Changchun 130012 China Institute of Computer Graphics and Image Processing Dalian Nationalities University No. 18 Liaohe Road Eco. and Tech. Dev. Zone Dalian 116600 China College of Computer Science and Engineering Dalian Nationalities University No. 18 Liaohe Road Eco. and Tech. Dev. Zone Dalian 116600 China College of Life Science Dalian Nationalities University No. 18 Liaohe Road Eco. and Tech. Dev. Zone Dalian 116600 China

Automatic image annotation is an active topic and difficult task in computer vision domain, which has attracted more and more researchers' attention. Many approaches have been proposed to automatically annotate images. To improve the annotation quality, most of them have profound principlessophisticated modelsand high time complexities. How to efficiently annotate image is becoming one key issue in the field of computer vision. We propose a very efficient and effective approach called keyword vector classification approach, whose model is very simple. Experiments on Corel5K dataset show that the annotation performance of the our proposed approach is almost four times better than translation model and twice better than CMRM (in terms of precision, recall and F1) while the time cost of ours surprisingly decreases. In addition, to our knowledge, our proposed approach outperforms most of existing ones in terms of N+. © 2011 ISSN 1881-803X.

关键词： Image retrieval

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key Value Ordering Heuristic for Solving Algorithm Based on the AC-4 Algorithm

Key Value Ordering Heuristic for Solving Algorithm Based on ...

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2010 International Conference on Computer,Mechatronics,Control and Electronic engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

作者： Zhan-shan Li Hai-jiao Shen Hui-ying Du Zi-wen Wang School of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University ChangchunChina

ISBN: (纸本)9781424479573

We have studied the AC-4 algorithm and then present key value ordering heuristic forming the new solving algorithm BT-KVV, which is based on the AC-4 algorithm. This algorithm takes full advantage of the state information of the data structure used in the AC-4 algorithm after the process of arc consistency. The algorithm sorts the values of the variables' domain according to the key importance of the values. So this order forces the solving algorithm to give priority to extend the key values of variables. In this way, the efficiency of the solving algorithm can be improved a lot. The result of our experiments shows that our algorithm has much more advantage over other solving algorithms.

关键词： arc consistency AC-4 value ordering heuristic solving algorithm key value

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Learning Essential Graph with Immune Co-Evolutionary Algorithm

Learning Essential Graph with Immune Co-Evolutionary Algorit...

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2010 International Conference of Informationa Science and Management engineering(2010年信息科学与管理工程国际学术会议 ISME 2010)

作者： Haiyang Jia Juan Chen Dayou Liu College of Computer Science and Technology Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin China 130012

Essential graph is a graphical representation for Markov equivalence classes of Bayesian networks. Learning essential graph can avoid some problems in traditional Bayesian networks learning algorithms: (1) the number of illegal structures is exponential, which infect the efficiency of structure learning;(2) comparing the structures in same equivalent class slow down the speed of convergence;(3) if the prior distribution for each structure is equal, the more structures contain in the equivalent class the higher prior probability of the class has. This paper employs two competitive bio-inspired algorithms, immune algorithm and co-evolutionary algorithm, for learning Essential graph. The algorithm combines dependency analysis and search-scoring approach together. Experiments show that the searching space was decreased, compare with prior works, the convergence speed and the efficiency was improved.

关键词： Bayesian network structure learining co-evolutionary algorithm artificial immune system

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A direction-based search algorithm in P2P network

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Journal of computational Information Systems 2010年第1期6卷 25-31页

作者： Liu, Xiaonan Fang, Zhiyi Tang, Huanhuan College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

We researched one search algorithm based on direction in the unstructured P2P network, analyzed the limited insufficiencies of this algorithm to the search speed, we proposed the improved direction search algorithm based on LAN agent-ABDS algorithm. We expounded the basic thought and the design principle of ABDS algorithm, carried on the theoretical analysis to the aspects of accuracy and parameter value. We took simulation experiments to the improved algorithms, carried on the quantification analysis to the improved algorithms through the experimental datum, drew up charts with the experimental datum, presented the network search process through the images, all which made the complex problems be more clearer and direct-viewing. Simulation experiments verify the improved algorithms improve the search speed of the P2P network, shorten the search response time. Copyright © 2010 Binary Information Press.

关键词： Learning algorithms

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A diversity-guided heuristic-based genetic algorithm for triangulation of Bayesian networks

A diversity-guided heuristic-based genetic algorithm for tri...

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International Conference on Networked Computing and Advanced Information Management (NCM)

作者： Xuchu Dong Haihong Yu Dantong Ouyang Yuxin Ye Yonggang Zhang Department of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun Jilin China

ISBN: (纸本)9781424476718

For the optimization problem about triangulation of Bayesian networks, a novel genetic algorithm, DHGA, is proposed in this paper. DHGA employs a heuristic-based mutation operation. Moreover, it uses population diversity to identify stagnation and convergence as well as to guide the search procedure. Experiments on representative benchmarks show that DHGA posses better performance and robustness than other swarm intelligence methods.

关键词： Bayesian methods

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