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International Conference on Information Science, Signal Processing and Their Applications

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

ISBN: (纸本)9780769541327

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. © 2010 IEEE.

关键词： Bayesian networks

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Model for human dynamics based on habit

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Chinese Science Bulletin 2010年第24期55卷 2744-2749页

作者： JIAO Yu LIU YanHeng WANG Jian WANG Jing 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 Archives of Jilin University Changchun 130012 China

The quantitative understanding of human behavior is a central question of modern science. Because of the complexity of human behavior, it is almost impossible to seek regularities in human dynamics. It is assumed that human actions are randomly distributed in time in current models for human dynamics. While the characteristics of human behavior combined with the queue model are considered as model for human dynamics based on habit to explain bursts and heavy tails in human dynamics more exactly. Normal distribution is used to simulate intervals of succession of events, and random parameters are set as unexpected events disturbing habit behaviors. Moreover, duration of events are proposed to imitate continual attention to some events in human behaviors.

关键词：人类行为基于模型动力学模型学习突发事件时间间隔现代科学随机分布

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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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2010 International Conference on Machine Vision and Human-Machine Interface, MVHI 2010

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

ISBN: (纸本)9780769540092

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. © 2010 IEEE.

关键词： Board boundary Composition Direction relations Model SK Uncertain regions Plant uncertain Uncertainty Modeling Boundary

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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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2010 2nd International Conference on Future Computer and Communication, ICFCC 2010

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

ISBN: (纸本)9781424458226

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 NEWHS-tree is an efficient hitting set algorithm proposed by Ouyang. RNHST proposed in this paper is a revised algorithm in respect of NEWHS-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. ©2010 IEEE.

关键词： Forestry

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Singleton arc consistency based on failure-first principle

Singleton arc consistency based on failure-first principle

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International Conference on Machine Learning and Cybernetics

作者： Li, Zhan-Shan Xing, Shi-Mei Yang, Feng-Jie Du, Hui-Ying Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China College of Computer Science and Technology Changchun 130012 China

ISBN: (纸本)9781424465262

Constraint satisfaction problems play a significant role in the field of Artificial Intelligence. Reducing the search space can improve the efficiency of solving the problems before the search of solutions. Applying in preprocessing step, arc consistency technique can remove some values which are arc inconsistent, so that it can reduce the search space. Using heuristic strategies can improve the efficiency of the algorithms. In this paper we propose a new singleton arc consistency algorithm based on failure-first principle, which improves the practical time efficiency through the earlier detection of variables which contain null values and removal of the values which are arc inconsistency during the preprocessing step. © 2010 IEEE.

关键词： Constraint satisfaction problems

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An improved particle swarm algorithms for global optimization

An improved particle swarm algorithms for global optimizatio...

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2010 International Conference on Machine Vision and Human-Machine Interface, MVHI 2010

作者： Tian, Ye Liu, Dayou College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China

ISBN: (纸本)9780769540092

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. © 2010 IEEE.

关键词： Global optimization

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Value ordering heuristic for solving algorithm based on the AC-4 algorithm

Value ordering heuristic for solving algorithm based on the ...

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2nd International Workshop on Intelligent Systems and Applications, ISA2010

作者： Li, Zhan-Shan Du, Hui-Ying Xing, Shi-Mei Meng, Fan-Wei School of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China

ISBN: (纸本)9781424458745

We have studied the AC-4 algorithm and then present value ordering heuristic for solving algorithm BT-MSV which is based on the AC-4 algorithm. This algorithm takes full advantage of supported information which is recorded in the data structure of the AC-4 algorithm during the process of arc consistency. The algorithm sorts the value of the variables' domain according to the supported information. So this order enforces the algorithm to extend the values of variables which have more support. In this way, the efficiency of the algorithm can be improved. The result of our experiments shows that our algorithm has much more advantage over other solving algorithms. ©2010 IEEE.

关键词： AC-4 Arc consistency Solving algorithm Value ordering heuristic

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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, CMCE 2010

作者： Li, Zhan-Shan Du, Hui-Ying Snen, Hai-Jiao Wang, Zi-Wen School of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

ISBN: (纸本)9781424479566

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. © 2010 IEEE.

关键词： AC-4 Arc consistency key value Solving algorithm Value ordering heuristic

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Improving incremental diagnosis with choosing measurement order

Improving incremental diagnosis with choosing measurement or...

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2010 International Conference of Information Science and Management engineering, ISME 2010

作者： Zhao, Xiangfu Ouyang, Dantong College of Mathematics Physical and Information Engineering Zhejiang Normal University Jinhua China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun China

ISBN: (纸本)9780769541327

There may be many groups of candidate results after the step of candidate generation in model-based diagnosis. Hwee Tou Ng proposed the Inc-Diagnose approach to further reduce the candidate results. However, the efficiency of Inc-Diagnose may not be very good. Firstly, we give some correction of Inc-Diagnosis by applying it to a real example. Then, we propose an improved approach with choosing the order of measurements for incremental diagnosis. Example results show that our approach has better efficiency. © 2010 IEEE.

关键词： Incremental diagnosis Measurement order Model-based diagnosis

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Interval-valued Fuzzy Description Logic IFALCN-Preliminary Results

Interval-valued Fuzzy Description Logic IFALCN-Preliminary R...

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2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

作者： Linlin Huo Jihong Ouyang Dayou Liu Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education College o Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education College of

To represent and reason with interval-value information of applications in description logic, based on interval-fuzzy set the classical description logic *** is extended to the fuzzy description logic IFALCN. Its' syntax, semantics and fuzzy tableau algorithm are presented in detail. Our work enhances the expressiveness and reasoning ability of ALCN. IFALCN is the generalization of fuzzy ALCN based on single value and more expressive than the latter and can conform to human cognition better.

关键词： description logic interval-value fuzzy set fuzzy tableau algotithm

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