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Adaptive Synchronization between Two Different Complex Networks with Time-Varying Delay Coupling

中国物理快报（英文版） 2009年第6期26卷 59-62页

作者： CHEN Jian-Rui JIAO Li-Cheng WU Jian-She WANG Xiao-Hua Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligence Information ProcessingXidian UniversityXi'an 710071 College of Science Inner Mongolia University of TechnologyInner Mongolia 01 Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligence Information ProcessingXidian UniversityXi'an 710071

A new general network model for two complex networks with time-varying delay coupling is *** we investigate its synchronization *** two complex networks of the model differ in dynamic nodes,the number of nodes and the coupling *** using adaptive controllers,a synchronization criterion is *** examples are given to demonstrate the effectiveness of the obtained synchronization *** study may widen the application range of synchronization,such as in chaotic secure communication.

关键词： No English Keywords

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Automatically organize web text resources with frequent term tree

Automatically organize web text resources with frequent term...

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IEEE 9th International Conference on Computer and information technology, CIT 2009

作者： Wang, Xiaofeng Shi, Zhongzhi Key Lab. of Intelligent Information Processing Institute of Computing Technology Graduate University of Chinese Academy of Sciences Beijing China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769538365

With the expansion of the Web, automatically organizing large scale text resources, e.g. Web pages, becomes very important. Many Web sites, like Google and Yahoo, use hierarchical classification trees to organize text resources in Web. User can easily find the text resources that meet their requirements by navigating these hierarchical classification trees. Typically, the text resources in Web are manually assigned to the nodes of the hierarchical classification tree. This limits the hierarchical classification tree to organize large scale text resources. In this paper, we propose a Frequent Term Tree to improve the ability of hierarchical classification tree in organizing large scale text resources in Web. Different from the Fp-tree [17] which is utilized to efficiently discover frequent patterns, the frequent term tree is used to organize resources with frequent pattern based classification. The Frequent Term Tree can accurately assign text resources to each node of classification tree and improve the ability in organizing resources with the incremental classified text resources. The evaluation of the Frequent Term Tree demonstrates that Frequent Term Tree can effectively and efficiently organize text resources. © 2009 IEEE.

关键词： Websites

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intelligent science 1

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12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular computing, RSFDGrC 2009

作者： Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Kexueyuan Nanlu #6 Beijing 100190 China

ISBN: (数字)9783642106460

ISBN: (纸本)3642106455

Intelligence Science is an interdisciplinary subject which dedicates to joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. Brain science explores the essence of brain, research on the principles and models of natural intelligence at molecular, cellular, and behavior levels. Cognitive science studies human mental activities, such as perception, learning, memory, thinking, consciousness etc. Artificial intelligence attempts simulation, extension, and expansion of human intelligence using artificial methods and technologies. Researchers specialized in above three disciplines work together to explore new concepts, theories, and methodologies. If successful, it will create a brilliant future in 21st century. The paper will outline the framework of intelligence science and present its ten big challenges. Tolerance Granular Space Model (TGSM) will be discussed as one of helpful approaches. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： Artificial intelligence

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Multi-objective optimization conceptual design of solar energy product based on hybrid genetic algorithm

Multi-objective optimization conceptual design of solar ener...

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International Conference on Computer Design and Applications (ICCDA)

作者： Tingting Zhao Zhenhe Ju Xiaopeng Wei Shi Zhang Shuaijie Wang Xiaoxiao Li School of Management Dalian University of Technology Dalian China Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China New Energy Center Shenyang Institute of Engineering Shenyang China Institute of Systems Engineering College of Information Science and Engineering Northeastern University Shenyang China Department of study Liaoning Solar Energy R and D Company Limited Shenyang China

ISBN: (纸本)9781424471645;9781424471638

For research on conceptual design of the complex product, it is necessary that a reliable theory is found to decide if the design structure is suit for custom requirement. The correlation matrixes among requirements, functions and structures are proposed. A block diagonal matrix of correlation matrix between functions and structures is given. The mathematical models of multi-object optimization structure design are provided, and then calculated by the hybrid genetic algorithm. An example for solar energy automobile is given to show that this method is able to realize optimization structure design fitting for the requirements. In addition, the approaches can provide good Pareto optimization solutions.

关键词： Design optimization Algorithm design and analysis Solar energy Genetic algorithms Genetic engineering Design engineering Power engineering and energy Mathematics Pareto optimization Reliability engineering

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Improving Tree-to-Tree Translation with Packed Forests

Improving Tree-to-Tree Translation with Packed Forests

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Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and 4th International Joint Conference on Natural Language processing of the AFNLP, ACL-IJCNLP 2009

作者： Liu, Yang Lü, Yajuan Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing100190 China

ISBN: (纸本)9781617382581

Current tree-to-tree models suffer from parsing errors as they usually use only 1-best parses for rule extraction and decoding. We instead propose a forest-based tree-to-tree model that uses packed forests. The model is based on a probabilistic synchronous tree substitution grammar (STSG), which can be learned from aligned forest pairs automatically. The decoder finds ways of decomposing trees in the source forest into elementary trees using the source projection of STSG while building target forest in parallel. Comparable to the state-of-the-art phrase-based system Moses, using packed forests in tree-to-tree translation results in a significant absolute improvement of 3.6 BLEU points over using 1-best trees. © 2009 ACL and AFNLP.

关键词： Decoding

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Lattice-based system combination for statistical machine translation

Lattice-based system combination for statistical machine tra...

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2009 Conference on Empirical Methods in Natural Language processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009

作者： Feng, Yang Liu, Yang Mi, Haitao Liu, Qun Lü, Yajuan Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China

Current system combination methods usually use confusion networks to find consensus translations among different systems. Requiring one-to-one mappings between the words in candidate translations, confusion networks have difficulty in handling more general situations in which several words are connected to another several words. Instead, we propose a lattice-based system combination model that allows for such phrase alignments and uses lattices to encode all candidate translations. Experiments show that our approach achieves significant improvements over the state-of-the-art baseline system on Chinese-to-English translation test sets. © 2009 ACL and AFNLP.

关键词： Natural language processing systems

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Weighted alignment matrices for statistical machine translation

Weighted alignment matrices for statistical machine translat...

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2009 Conference on Empirical Methods in Natural Language processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009

作者： Liu, Yang Xia, Tian Xiao, Xinyan Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China

Current statistical machine translation systems usually extract rules from bilingual corpora annotated with 1-best alignments. They are prone to learn noisy rules due to alignment mistakes. We propose a new structure called weighted alignment matrix to encode all possible alignments for a parallel text compactly. The key idea is to assign a probability to each word pair to indicate how well they are aligned. We design new algorithms for extracting phrase pairs from weighted alignment matrices and estimating their probabilities. Our experiments on multiple language pairs show that using weighted matrices achieves consistent improvements over using n-best lists in significant less extraction time. © 2009 ACL and AFNLP.

关键词： Alignment

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Joint Decoding with Multiple Translation Models

Joint Decoding with Multiple Translation Models

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Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and 4th International Joint Conference on Natural Language processing of the AFNLP, ACL-IJCNLP 2009

作者： Liu, Yang Mi, Haitao Feng, Yang Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing100190 China

ISBN: (纸本)9781617382581

Current SMT systems usually decode with single translation models and cannot benefit from the strengths of other models in decoding phase. We instead propose joint decoding, a method that combines multiple translation models in one decoder. Our joint decoder draws connections among multiple models by integrating the translation hypergraphs they produce individually. Therefore, one model can share translations and even derivations with other models. Comparable to the state-of-the-art system combination technique, joint decoding achieves an absolute improvement of 1.5 BLEU points over individual decoding. © 2009 ACL and AFNLP.

关键词： Decoding

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THE EFFECT OF SCALE TRANSFORMATION FOR HYPER SURFACE CLASSIFICATION METHOD

THE EFFECT OF SCALE TRANSFORMATION FOR HYPER SURFACE CLASSIF...

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2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

作者： QING HE ZHONG-ZHI SHI XU-DONG MA FU-ZHEN ZHUANG The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese

Hyper Surface Classification (HSC), which is based on Jordan Curve Theorem in Topology, has been proven to be a simple and effective method for classifying a large database in our previous work. In this paper, through theoretical analysis, we find that different scales may affect the training process of HSC, which influences its classification performance. To investigate the impact and find a suitable scale, the scale transformation of HSC is studied. The experimental results show that the accuracy increases with the shrinkage of the scale, but the effect is tiny. Furthermore, we find that some samples become inconsistent and repetitious when the scale is adequately small, because of the powerlessly providing enough precision by the data type of computer. Fortunately, HSC can get a high performance with common scales as experiments exhibit.

关键词： Hyper Surface Classification HSC Scale Transformation

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Unusual Pattern Detection Based on Hyper Surface and Minimum Spanning Tree

Unusual Pattern Detection Based on Hyper Surface and Minimum...

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2009 IEEE International Conference on information and Automation(2009年 IEEE信息与自动化国际学术会议)

作者： Qing He Weizhong Zhao Jincheng Li Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese A The Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese A

More analysis has been done to discover the meaningful unusual patterns which may mean fraud or anomaly. In this paper, a novel unsupervised approach for discovering meaningful unusual observations is proposed. We firstly apply an unsupervised version of Hyper Surface Classification (HSC) algorithm to gain the separating hyper surface. It needs no domain knowledge but can not discover the local unusual pattern. To solve this problem, we additionally search the Minimum Spanning Tree (MST). Given the domain knowledge, a process of subdividing is proposed to detect unusual pattern in each Minimum Spanning Tree. Experimental results show that our approach can detect unusual patterns effectively, even some of which are overlooked by using the traditional clustering and outlier detection algorithms.

关键词： Detection algorithms Credit cards Pattern analysis Face detection Predictive models Automation Laboratories information processing Computers information analysis

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