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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： JIAN GAO YONG-GANG ZHANG JI-GUI SUN College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education Changchu

In recently years there has been plenty of interest in Random Constraint Satisfaction Problem, both from an experimental and a theoretical point of view. In this paper we study and analyze the four popular problem instance generating models, and present the extended model B+ based on the most used model B, which has the different domains and constraint tightness meeting some probability distribution function. In the subsequent section we give the relation matrix version of backtracking integrated forward checking algorithms, and introduce the implementation of instances generator and solver based on the new model. Finally we show the experiment results and conclude the paper, point that our extended model B+ has the common phase transition region with the transitional models and it has the advantage of being suited to the testing of heuristic based constraint solving algorithms, such as variables selection heuristic algorithms.

关键词： Constraint programming RCSP constraint solving generating model testing

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Diagnosis of breast cancer tumor based on ICA and LS-SVM

Diagnosis of breast cancer tumor based on ICA and LS-SVM

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2006 International Conference on Machine Learning and Cybernetics

作者： Wang, Chao-Yong Wu, Chun-Guo Liang, Yan-Chun Guo, Xin-Chen Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China Department of Fundamental Sciences Jilin Teacher's Institute of Engineering and Technology Changchun 130021 China Key Laboratory of Information Science and Engineering Beijing Jiaotong University Railway Ministry Beijing 100044 China

ISBN: (纸本)1424400619

An efficient method for the diagnosis of breast cancer tumor is proposed based on Independent Component Analysis (ICA) and Least Square Support Vector Machine (LS-SVM). In order to save the expense of detection, firstly, variables are selected based on the theory of statistics. Then the ICA is introduced in a concise way and followed by extracting the ICA component from these selected variables. Finally the processed data are classified by the LS-SVM. Experimental and analytical results show that in the diagnosis of breast cancer tumor the proposed method is superior to the classical B-P algorithm. © 2006 IEEE.

关键词： Biomedical engineering

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STUDIES ON SOME DETAILS OF ALGORITHM IGRS

STUDIES ON SOME DETAILS OF ALGORITHM IGRS

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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： CHUN-XIAO FU SHU-YANG SUN CHENG-MIN SUN DA-YOU LIU College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin Uni

In Containing Order Rough Set Methodology (CORS),terminologies on rules or rules set, such as robust, minimality,completeness, mutuality degree, and conflict are discussed. The rules generation algorithm IGRs is given and the details of algorithm IGRs are studied. Heuristic knowledge, which is mutuality degree of a condition item with a decision part, is used to choose condition item when generating rules. In primary and modified IGRs, two kinds of mutuality degree,simple and weighted mutuality are introduced respectively. In addition, the variable precision method is used to solve the conflict problem in modified IGRs. By experiments, the effects of two kinds heuristic knowledge and different weight values in synthetic mutuality on algorithms properties are shown,such as time consumption, calculation precision etc. The performances of IGRs with the primary and new conflict solution are compared by experiments. The conclusion is that the weighted mutuality degree is more sound and the choice of appropriate weight values in it are important to optimize the quality of rules set. The variable precision method for dealing with conflict when generating rules is more reasonable. Both two modifications to primary IGRs make the performance of IGRs enhanced and the quality of rules set better. Algorithm IGRs still need further improvement.

关键词： Criteria Dominance relation Algorithm IGRs Mutuality degree Conflict

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Algorithm Studies of Rules Generation in CORS

Algorithm Studies of Rules Generation in CORS

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Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

作者： Chunxiao Fu Shuyang sun Chengmin Sun Dayou Liu College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin Uni

ISBN: (纸本)1424404754

In Containing Order Rough Set Methodology (CORS), ordered attribute 'criterion' is introduced. Criterion is related semantically with decision attributes, which results in producing more rational and significant rules utilizing dominance relations. In this paper, some terminologies and properties on rules or rules set, such as robust, minimal, complete are discussed, the state of art in algorithms on rules generation are analyzed, and algorithms GRs and IGRs are proposed. We compare these two algorithms by experiments in time complexity, rules count and accuracy. We find that GRs can generate all minimal rules, but time complexity is high and IGRs' efficiency is better, but quality of rules are inferior to that of GRs. We also discuss the completeness of rules set and present a viewpoint that there are three hierarchies for completeness. In accuracy calculation, three formulas for accuracy calculation and two approaches for experimental test are given.

关键词： Criteria Dominance relation Algorithm GRs Algorithm IGRs Completeness

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Support vector machine regression algorithm based on chunking incremental learning

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ICCS 2006: 6th International Conference on computational Science

作者： Jingqing, Jiang Chuyi, Song Chunguo, Wu Maurizio, Marchese Yangchun, Liang Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China College of Mathematics and Computer Science Inner Mongolia University for Nationalities Tongliao 028043 China Key Laboratory of Information Science and Engineering Beijing Jiaotong University Railway Ministry Beijing 100044 China Italy

ISBN: (纸本)3540343792

On the basis of least squares support vector machine regression (LSSVR), an adaptive and iterative support vector machine regression algorithm based on chunking incremental learning (CISVR) is presented in this paper. CISVR is an iterative algorithm and the samples are added to the working set in batches. The inverse of the matrix of coefficients from previous iteration is used to calculate the regression parameters. Therefore, the proposed approach permits to avoid the calculation of the inverse of a large-scale matrix and improves the learning speed of the algorithm. Support vectors are selected adaptively in the iteration to maintain the sparseness. Experimental results show that the learning speed of CISVR is improved greatly compared with LSSVR for the similar training accuracy. At the same time the number of the support vectors obtained by the presented algorithm is less than that obtained by LSSVR greatly. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Learning systems

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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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Visualization model of fuzzy region based on pleat set

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Xitong Fangzhen Xuebao / Journal of System Simulation 2006年第SUPPL.期18卷 340-342+346页

作者： Wu, De-Sheng Yu, Qiang-Yuan Institute of Information Spreading Engineering Changchun University of Technology Changchun 130012 China 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

Fuzziness modeling for spatial data is currently an important problem in geographic information systems and spatial databases. In many geographical applications, spatial regions do not always have sharply defined boundaries but frequently their interiors and boundaries are fuzzy. A fuzzy spatial region model was proposed based on pleat set and the property of fuzzy regions was analyzed. The calculation method of relative membership of point in fuzzy region was given, and visualization model based on absolute membership value was proposed. The practical case shows that the model based on pleat set is valuable in the fields such as GIS, geography and spatial database.

关键词： Fuzzy region GIS Pleat set Visualization

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Performance Evaluation of JXTA Based P2P Distributed Computing System

Performance Evaluation of JXTA Based P2P Distributed Computi...

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International Conference on Computing (CIC)

作者： Zhiming Dai Zhiyi Fang Xiao Han Fengyuan Xu Hongjun Yang School of Computer Science and Technology Key Laboratory Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China School of Economics and Information Systems Jilin University China

In this paper, we introduce the condition of distributed computing at present firstly. On this foundation, according to the analysis of particular case of distributed computing network, we implement a distributed network environment of P2P whose bottom layer frame is based on JXTA. It improves issuing method of message based on pipeline decomposition mechanism of task based on usage ratio of processor and distributed mechanism of object based on serialization. We build an improved distributed computing network platform on the platform of Linux and Windows and simulate a distributed computing environment. The simulated experiment proves the feasibility and the validity of the distributed network computing platform that is constructed in this paper

关键词： Distributed computing Peer to peer computing Computer networks computational modeling Protocols Power generation economics Environmental economics Linux Large-scale systems Application software

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AN EFFICIENT COLLISION DETECTION OF COMPLEX DEFORMABLE OBJECTS BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM

AN EFFICIENT COLLISION DETECTION OF COMPLEX DEFORMABLE OBJEC...

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2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： YI WANG WEN-HUI LI TIAN-ZHU WANG WU GUO ZHEN-HUA ZHANG Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education College of Computer Science and Technology Jilin University 130012 ChangChun P.R.China

A technique for performing collision detection between complex deformable objects by using PSO optimizer is demonstrated. This approach provides a more comprehensive way to trade-off accuracy for computation time. Although the swarm can handle temporal coherence and efficiently search through the highly large primitive pair solution space, we combine it with hierarchies to achieve higher culling efficiency and significantly reduce the size of solution space. At last, we give the precision and efficiency evaluation about the algorithm and find it might be a reasonable choice for deformable models in collision detection systems.

关键词： Collision Detection Bounding Volumes Hierarchies Particle Swarm Optimization

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A dynamic time delay neural network for ultrasonic motor identification and control

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

作者： Liang, Yanchun Zhang, Jie Xu, Xu Yang, Xiaowei Hao, Zhifeng Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China College of Mathematics Jilin University Changchun 130012 China School of Mathematical Science South China University of Technology Guangzhou 510640 China

ISBN: (纸本)3540344373

A novel dynamic time delay neural network is proposed for ultrasonic motors identification and control in this paper. By introducing time delay neurons, the neural network identifier and controller of ultrasonic motors are constructed. Both of them are trained online by using an improved back-propagation algorithm. The usefulness and validity of the presented algorithm is examined by the experiments. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Neural networks

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