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6th International Conference on Intelligent Systems Design and Applications (ISDA 2006)

作者： Chang, Xiao-Yu Zhou, Chun-Guang Li, Yan-Wen Hu, Ping Key Laboratory of Symbol Computation and J Knowledge Engineering Jilin University Ministry of Education China Department of Computer Science Northeast Normal University Changchun 130012 China

ISBN: (纸本)0769525288

Identification of transcription factor binding sites from the upstream regions of genes is a highly important and unsolved problem. In this paper, we propose a novel framework for using evolutionary algorithm to solve this challenging issue. Under this framework, we use two prevalent evolutionary algorithms: Genetic, Algorithm (GA) and Particle Swarm Optimization (PSO) to find unknown sites in a collection of relatively long intergenic sequences that are suspected of being bound by the same factor. This paper represents binding sites motif to position weight matrix (PWM) and introduces how to code PWM to genome for GA and how to code it to particle for PSO. We apply these two algorithms to 5 different yeast Saccharomyces Cerevisiae transcription factor binding sites and CRP binding sites. The results on Saccharomyces Cerevisiae show that it can find the correct binding sites motifs, and the result on CRP shows that these two algorithms can achieve more accuracy than MEME and Gibbs Sampler.

关键词： Binding sites

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Modeling and refining directional relations based on fuzzy mathematical morphology

Modeling and refining directional relations based on fuzzy m...

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High-Power Diode Laser Technology and Applications IV

作者： Sun, Haibin Li, Wenhui Key Laboratory of Symbol Computation Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun 130012 China

ISBN: (纸本)0819461466

In this paper, we investigate the deficiency of Goyal and Egenhofer's method for modeling cardinal directional relations between simple regions and provide the computational model based on the concept of mathematical morphology, which can be a complement and refinement of Goyal and Egenhofer's model for crisp regions. Based on fuzzy set theory, we extend Goyal and Egenhofer's model to handle fuzziness and provide a computational model based on alpha-morphology, which combines fuzzy set theory and mathematical morphology, to refine the fuzzy cardinal directional relations. Then the computational problems are investigated. We also give an example of spatial configuration in 2-dimensional discrete space. The experiment results confirm the cognitive plausibility of our computational models. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Fuzzy sets

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Fuzzy neural network optimization by a particle swarm optimization algorithm

Fuzzy neural network optimization by a particle swarm optimi...

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3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Ma, Ming Zhang, Li-Biao Ma, Jie Zhou, Chun-Guang Key Laboratory for Symbol Computation and Knowledge Engineering Jilin University National Education Ministry of China Changchun 130012 China Information Manage Center Beihua University Jilin 132013 China

ISBN: (纸本)354034439X

Designing a set of fuzzy neural networks can be considered as solving a multi-objective optimization problem. An algorithm for solving the multi-objective optimization problem is presented based on particle swarm optimization through the improvement of the selection manner for global and individual extremum. The search for the Pareto Optimal Set of fuzzy neural networks optimization problems is performed, Numerical simulations for taste identification of tea show the effectiveness of the proposed algorithm. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Neural networks

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Application of qualitative spatial reasoning in computer games

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Journal of computational Information Systems 2006年第2期2卷 505-511页

作者： Wang, Shengsheng Wang, Xinying Liu, Dayou Liu, Jie College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Changchun 130012 China

To improve artificial intelligence (AI) of computer games is a hard problem. Qualitative spatial reasoning is utilized to solve this problem. In qualitative spatial reasoning various aspects of qualitative spatial reasoning such as topology, direction, size and distance have been widely investigated in pervious literatures. Although, the combination works of two or more spatial aspects are more useful than the single one in computer game and other applications, most combining problems have not been discussed before. So a unified model for qualitative topology and distance information is proposed. Finally this method is applied to strategy computer games.

关键词： Artificial intelligence

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An efficient method for very large scale out-of-core terrain visualization

An efficient method for very large scale out-of-core terrain...

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16th International Conference on Artificial Reality and Telexistence - Workshops, ICAT 2006

作者： Zhang, Huijie Sun, Jigui Yu, Haihong Qi, Changsong College of Computer Science and Technology Jilin University College of Computer Science Northeast Normal University Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education

ISBN: (纸本)076952754X

Large scale terrain visualization with high-resolution has an increasing demand in many research fields. To realize the efficient rendering of terrain, this paper presents an out-of-core terrain visualization method based on multi-resolution storage techniques. In external memory, the terrain data set is subdivided from top to bottom to build a multi-resolution hierarchical structure based on a quad-tree. The hierarchical structure can decimate the elevation data that must be loaded into internal memory. Thus it can improve the efficiency of I/O access greatly. Moreover, in order to implement rapid data retrieval of the real time terrain flyover, an efficient indexing algorithm is proposed, in which those nodes in the hierarchical structure will be divided into several clusters in terms of the similarities of static error and the closed space constraint. In addition, a method for crack-free is also proposed here. The comprehensive experiment conducted on the GTOP30 data set shows that this approach outperforms the Block and the Hierarchy algorithms in the both ways of efficiency and simplification ratio. © 2006 IEEE.

关键词： Efficiency

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A hybrid discrete particle swarm algorithm for open-shop problems

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6th International Conference Simulated Evolution and Learning, SEAL 2006

作者： Qingyun, Yang Jigui, Sun Juyang, Zhang Chunjie, Wang College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China Open Laboratory for Intelligence Information Processing Fudan University Shanghai 200433 China Basic Sciences of ChangChun University of Technology ChangChun University of Technology Changchun 130012 China

ISBN: (纸本)3540473319

A hybrid discrete particle swarm algorithm is presented in this paper to solve open-shop problems. The operations are redefined in the discrete particle swarm algorithm. To improve the performance the simulated annealing algorithm is combined with discrete particle swarm. We use SA to enhance the results of local best positions instead of current positions. The experimental results show that our hybrid discrete particle swarm algorithm is effective and efficient to solve open-shop problems. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Open systems

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The Newton interpolation bases on lower sets

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Journal of Information and computational Science 2006年第3期3卷 385-394页

作者： Chen, Tao Dong, Tian Zhang, Shugong Key Lab. of Symbolic Computation and Knowledge Engineering Institute of Math. Jilin University Changchun 130012 China

Newton's algorithm for constructing univariate interpolation polynomial is well-known. In this paper, we generalize Newton's formula to multivariate Lagrange interpolation. For some type of subset ΧL, so-called lower subset, of a tensor product grid, we present directly an interpolation basis of Newton type which spans a minimal degree interpolation space for Lagrange interpolation on ΧL. We show that this basis is always a Newton interpolation basis for arbitrary ordered set of point evaluation functionals.

关键词： Interpolation

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SLNN: A Neural Network for Fuzzy Neural Network's Structure Learning

SLNN: A Neural Network for Fuzzy Neural Network's Structure ...

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International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Daxin Tian Yanheng Liu Jian Wang College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China

A novel structure learning algorithm for fuzzy neural networks (SLNN) is presented in this paper. The neurons of SLNN are created and adapted as online learning proceeds. The learning rule of SLNN is based on Hebbian learning and a kernel winner-take-all algorithm - KWTA. KWTA not only can let SLNN be able to learn from new data but also can prevent losing the knowledge which has been learned earlier. To obtain a concise fuzzy rule, a pruning algorithm is adopted in SLNN which doesn't disobey the basic design philosophy of fuzzy system. Simulations are performed on the primary benchmark: circle-in-the-square. Comparison with ARTMAP and BP neural network indicates that better performance is achieved

关键词： Neural networks Fuzzy neural networks Fuzzy systems Clustering algorithms Signal processing algorithms Computer networks Neurons Partitioning algorithms Learning Fuzzy control

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Research of Mobile IPv6 Application Based On Diameter Protocol

Research of Mobile IPv6 Application Based On Diameter Protoc...

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International Multi-Symposiums on Computer and computational Sciences (IMSCCS)

作者： Da Wei Yanheng Liu Xuegang Yu Xiaodong Li College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China

The diameter protocol is recommended by IETF as AAA (authentication, authorization and accounting) protocol criterion for the next generation network. Because the IPv6 protocol will be widely applied in the intending all-IP network, mobile IPv6 application based on diameter protocol will play more important role in authentication, authorization and accounting. In this paper, the implementation of mobile node's authentication and authorization is presented with PANA (protocol for carrying authentication for network access) protocol. It is based on diameter protocol for the application expansion of mobile IPv6, which provides the supports to the basic AAA process of mobile IPv6 nodes and dynamic home agent distribution in the visited network and the secret key distribution. Finally, the correctness of this application expansion is testified with developing the design of protocol based on opendiameter

关键词： Access protocols Authentication Cryptographic protocols Authorization Network servers Application software IP networks Peer to peer computing Transport protocols Computer science

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A Dynamic Growing Neural Network for Supervised or Unsupervised Learning

A Dynamic Growing Neural Network for Supervised or Unsupervi...

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World Congress on Intelligent Control and Automation (WCICA)

作者： Daxin Tian Yanheng Liu Da Wei College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin China

A dynamic growing neural network (DGNN) for supervised learning of pattern recognition or unsupervised learning of clustering is presented. The main ideas included in DGNN are growing, resonance, and post-prune. DGNN is called dynamic growing because it is based on the Hebbian learning rule and adds new neurons under certain conditions. When DGNN performs supervised learning, resonance will happen if the winner can't match the training example; this rule combines the ART/ARTMAP neural network and WTA learning rule. When DGNN performs unsupervised learning, post-prune is carried out to prevent over fitting the training data just like decision tree learning. DGNN's prune rule is based on the distance threshold. DGNN has some advantages: learning not only is stable because it grows under certain conditions; but also it is faster than back-propagation rules and favorable learned predictive accuracy in small, noisy, online or offline data sets. Three classes of simulations are performed on the primary benchmarks: circle-in-the-square and two-spirals-apart benchmarks are used to check DGNN's supervised learning and compare it with ARTMAP and BP neural networks; DGNN's unsupervised learning ability is checked on UCI Machine Learning Archive's Synthetic Control Chart Time Series data set

关键词： Neural networks Unsupervised learning Supervised learning Resonance Pattern recognition Hebbian theory Neurons Subspace constraints Training data Decision trees

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