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3rd International Conference on Natural Computation, ICNC 2007

作者： Pu, Yan Dayou, Liu Donghui, Yuan Ji, Yu Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)0769528759

In this paper, a genetic algorithm approach with a novel mutation operator based on perturbation and local search has been proposed to solve an advanced planning and scheduling (APS) model in manufacturing supply chain, in which each customer order has a due date, each operation could be performed on alternative machines. The objective is to minimize the makespan of each customer order while ensuring the due date constraints. Various sizes of numerical experiments were carried out to demonstrate the efficiency of the proposed GA and the results indicate that the presented algorithm performs much better than previous work especially in large size problems. © 2007 IEEE.

关键词： Genetic algorithms

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Graph-based fast image segmentation

Graph-based fast image segmentation

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Joint IAPR International Workshops on Structural, Syntactic, and Statistical Pattern Recognition, SSPR 2006 and SPR 2006

作者： Han, Dongfeng Li, Wenhui Lu, Xiaosuo Li, N. Wang, Yi Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)3540372369

In this paper, we describe a fast semi-automatic segmentation algorithm. A nodes aggregation method is proposed for improving the running time and a Graph-Cuts method is used to model the segmentation problem. The whole process is interactive. Once the users specify the interest regions by drawing a few lines, the segmentation process is reliably computed automatically no additional users' efforts are required. It is convenient and efficient in practical applications. Experiments are given and outputs are encouraging. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Image segmentation

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DualRank: A dual-phase algorithm for optimal profit mining in retailing market

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10th Asian Computing Science Conference, ASIAN 2005

作者： Xu, Xiujuan Jia, Lifeng Wang, Zhe Zhou, Chunguang Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China

ISBN: (纸本)3540307672

We systematically propose a dual-phase algorithm, DualRank, to mine the optimal profit in retailing market. DualRank algorithm has two major phases which are called mining general profit phase and optimizing profit phase respectively. In the first phase, the novel sub-algorithm, ItemRank, integrates the random distribution of items into profit mining to improve the performance of item order. In the other phase, two novel optimizing sub-algorithms are proposed to ameliorating results generated in the first phase. According to the cross-selling effect and the self-profit of items, DualRank algorithm could solve the problem of item order objectively and mechanically. We conduct detailed experiments to evaluate DualRank algorithm and experiment result confirms that the new method has an excellent ability for profit mining and the performance meets the condition which requires better quality and efficiency. © Springer-Verlag Berlin Heidelberg 2005.

关键词： data mining

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Solving job-shop scheduling problems by a novel artificial immune system

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18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence

作者： Ge, Hong-Wei Sun, Liang Liang, Yan-Chun Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China

ISBN: (纸本)3540304622

The optimization of job-shop scheduling is very important because of its theoretical and practical significance. This paper proposes an efficient scheduling method based on artificial immune systems. In the proposed method, the initial population is generated by a proposed scheduling initialization algorithm based on the G&T algorithm, and the models of the vaccination and receptor editing are designed to improve the immune performance. The approach is tested on a set of standard instances taken from the existing standard library. The simulation results validate the effectiveness of the proposed algorithm. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Intelligent networks

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A new position updating algorithm for moving objects

A new position updating algorithm for moving objects

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First International Multi- Symposiums on Computer and Computational Sciences, IMSCCS'06

作者： Xinying, Wang Shengsheng, Wang Zhengxuan, Wang Tianyang, Lv Xizhe, Zhang Key Laboratory of Symbolic Computing and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China

ISBN: (纸本)0769525814

Continuous queries are important in moving objects databases and spatio-temporal reasoning. The traditional synchronous updating algorithms of moving object pervasively focus on improving queries' execution efficiency, while ignore the fact that the communication cost is also the bottleneck for improving query efficiency. We propose an asynchronous updating algorithm for continuous queries of moving objects. Three types of continuous range queries are discussed in the paper. Theoretical analysis and experiment results show that our algorithm substantially outperforms the traditional synchronous updating algorithms at aspects of monitoring accuracy, communication cost and CPU load balance. © 2006 IEEE.

关键词： Algorithms

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Complex knowledge system modeling based on Hierarchical Fuzzy Petri Net

Complex knowledge system modeling based on Hierarchical Fuzz...

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2007 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2007

作者： Hongjun, Pan Jigui, Sun Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China

ISBN: (纸本)0769530281

The difficulties of modeling complex knowledge system lie in a large quantity of knowledge rules and the difficulty in organizing rules and grasping their mutual logical relationships. This article proposed a concept of hierarchical fuzzy Petri nets (HFPN), which is more suitable for modeling complex knowledge system than other fuzzy Petri Net models. In addition, the concepts of abstract place and abstract transition in HFPN are allowed to describe and analyze the knowledge system at diverse abstract levels. Therefore, using HFPN, the iterative and incremental methods can be applied to modeling complex knowledge system. In addition, structured approach can be naturally applied to the process of modeling knowledge system. © 2007 IEEE.

关键词： Petri nets

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RETRACTED ARTICLE: The IDS model adapt to load characteristic under IPv6/4 environment

RETRACTED ARTICLE: The IDS model adapt to load characteristi...

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2008 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2008

作者： Wei, Chuyi Fang, Zhiyi Li, Wei Liu, Xiaonan Yang, Hongjun Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China

ISBN: (纸本)9781424421084

Thih paper proposed an intrusion detection system framework adapt to load characteristic under IPv6/4 environment; it uses decision-tree-based classification method, under guidance of a certain flow, creates dynamically rule matching tree adapt to load characteristic, reduces greatly the rule set that per packet or event need to be detected, improves the detection efficiency, can be utilized to solve the high packetloss problem; this paper proposed to make use of Petri net to built a mode to the complicated aggressive behavior, form the complicated aggressive rule library, improve the detection accuracy rate; in view of IPv6 security problem, make use of Snort rule description language, construct the detection rule under IPv6 environment; finally construct the platform in the local area network, carry on the simulation experiment. The experiment proved fully the feasibility and validity of intrusion detective method adapt to load characteristic under IPv6/4 environment. © 2008 IEEE.

关键词： Intrusion detection

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An adaptive stochastic collision detection between deformable objects using particle swarm optimization

An adaptive stochastic collision detection between deformabl...

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EvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC

作者： Tianzhu, Wang Wenhui, Li Yi, Wang Zihou, Ge Dongfeng, Han Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China

ISBN: (纸本)3540332375

In this paper, we present an efficient method for detecting collisions between highly deformable objects, which is a combination of newly developed stochastic method and Particle Swarm Optimization (PSO) algorithm. Firstly, our algorithm samples primitive pairs within the models to construct a discrete binary search space for PSO, and in this way user can balance performance and detection quality. Besides a particle update process is added in every time step to handle the dynamic environments caused by deformations. Our algorithm is also very general that makes no assumptions about the input models and doesn't need to store additional data structures either. In the end, we give the precision and efficiency evaluation about the algorithm and find it might be a reasonable choice for complex deformable models in collision detection systems. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Intelligent agents

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Gaining water bodies by climate change benefits water crisis mitigation in central Asia

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Science Bulletin 2025年

作者： Su, Yanan Chen, Shengqian Sui, Yijie Li, Xin Xu, Jinhao Che, Xianghong Xie, Tingting Chen, Jianhui Sheng, Yongwei Feng, Min Chen, Fahu State Key Laboratory of Tibetan Plateau Earth System Environment and Resources Institute of Tibetan Plateau Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing100049 China Research Center of Geospatial Big Data Application Chinese Academy of Surveying and Mapping Beijing100830 China College of Water Resources and Architectural Engineering Tarim University Alar843300 China Key Laboratory of Western China's Environmental Systems Ministry of Education College of Earth and Environmental Sciences Lanzhou University Lanzhou730000 China Department of Geography University of California Los AngelesCA90095 United States Academy of Plateau Science and Sustainability Qinghai Normal University Xining810016 China

Central Asia (CA) faces a severe water crisis exemplified by the shrinking Aral Sea. However, little is known about the entire region, particularly the numerous small water bodies that are vulnerable to climate change yet vital for regional sustainability. We examined water bodies as small as 0.0045 km2 across CA from 1992 to 2020, identifying 66,215 water bodies in 2020, 82.2% of which were previously unstudied. In contrast to the well-documented decline of the Aral Sea, other water bodies have expanded by 10.7% (8714.3 km2), with a net gain of 15,831 lakes since 1992. These findings challenge the perception of a drying CA and provide evidence of a warm-wet climate trend, which is redistributing water resources and creating opportunities for transforming water management to address the long-standing water crisis in CA. © 2025 Science China Press

关键词： Central Asia Climate Change Small Water Bodies Water Crisis Water Resource Management

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A novel method for mining sequential patterns in datasets

A novel method for mining sequential patterns in datasets

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ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications

作者： Xiaoyu, Chang Chunguang, Zhou Zhe, Wang Ping, Hu Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun 130012 China

ISBN: (纸本)0769525288

Sequential pattern mining is one of the most important fields in data mining. In this paper, we propose a novel algorithm FSPAN (Fast Sequential Pattern mining algorithm) to do the sequence mining. FSPAN can mine all the frequent sequential patterns in large datasets and it integrates a depth-first traversal approach with an effective pruning mechanism. This pruning mechanism solves the problem of searching frequent sequences in a sequence database by searching frequent items or frequent itemsets, which makes this method very efficient. Moreover, the databases scanned via FSPAN keep shrinking quickly, which makes the algorithm more efficient when the sequential patterns are longer. Experiments on standard test data show that FSPAN is very effective. © 2006 IEEE.

关键词： data mining

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