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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ya-Bo Liu Da-You Liu Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Jilin University Changchun Jilin CN Coll. of Comput. Sci. & Technol. Jilin Univ. Changchun China

It is well recognized that sequential pattern mining plays an essential role in many scientific and business domains. In this paper, a new extension of sequential pattern, attributes' sequential pattern, is proposed. An attributes' sequential pattern is a sequence of attributes, whose values commonly occur in ascending order over data set. After each record in data set is transformed into an attributes' sequence according to their ordinal values, attributes' sequential patterns can be mined by means of mining sequential patterns. But our work is different from sequential pattern mining. One use of attributes' sequential patterns is to identify possible errors in data set for data cleaning, in which the values of attributes break the attributes' sequential patterns which most of the data conform to. Experiments verify the high efficiency of the method presented.

关键词： Cleaning Data mining Diseases Itemsets Computer errors Pattern recognition educational institutions Computer science educational technology Laboratories

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Nondestructive quantitative analysis of compound paracetamol and diphenhydramine hydrochloride powder using RBF networks

Nondestructive quantitative analysis of compound paracetamol...

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International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Zheng, Hong Wan, Li.-Ming Jiang, Jing-Qing Liang, Yan-Chun Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China College of Computer Science and Engineering Changchun University of Technology Changchun 130012 China Institute of General Development and Evaluation of Equipment EAAF of PLA Beijing 100076 China College of Mathematics and Computer Science Inner Mongolia University for Nationalities Tongliao 028043 China

ISBN: (纸本)078039092X

A method for simultaneous analysis of the two components of compound paracetamol and diphenhydramine hydrochloride powdered drugs on near-infrared (NIR) spectroscopy is developed by using a Radial Basis Function (RBF) network. Nearest neighbor-clustering algorithm is used as the learning algorithm of RBF network. Comparisons of the results obtained from the RBF models with those from BP models show that it is feasible to use the RBF network in nondestructive quantitative analysis of the components of drugs. © 2005 IEEE.

关键词： Neural networks

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Medicine composition concentration analysis based on least square support vector machine

Medicine composition concentration analysis based on least s...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Xin-Chen Guo Zhou-Yi Chen Li-Rong Teng Chun-Guo Wu Tian-Bao Du Jia-Huilu Qing-Fan Meng Yan-Chun Liang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun China College of Science Northeast China Institute of Electric Power Engineering Jilin China EAAF of PLA Institute of General Development and Evaluation of Equipment Beijing China College of Life Science Jilin University Changchun China

This paper presents a method of medicine composition concentration analysis based on least square support vector machines (LS-SVMs) and examines the importance of the hyperparameter choice in improvement of algorithm performance. Simulation results show that the proposed method obtains high quality precision in the generalization, compared with multiple linear regression, and that it is an efficient approach to regression estimation.

关键词： Least squares methods Support vector machines educational institutions Performance analysis Algorithm design and analysis knowledge engineering Linear regression Spectral analysis Quadratic programming Lagrangian functions

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Nondestructive quantitative analysis of compound paracetamol and diphenhydramine hydrochloride powder using RBF networks

Nondestructive quantitative analysis of compound paracetamol...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Hong Zheng Li-Ming Wan Jing-Qing Jiang Yan-Chun Liang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China College of Computer Science and Engineering Changchun University of Technology Changchun China Institute of General Development and Evaluation of Equipment EAAF of PLA Beijing China College of Mathematics and Computer Science Inner Mongolia University for the Nationalities Tongliao China

A method for simultaneous analysis of the two components of compound paracetamol and diphenhydramine hydrochloride powdered drugs on near-infrared (NIR) spectroscopy is developed by using a radial basis function (RBF) network. Nearest neighbor-clustering algorithm is used as the learning algorithm of RBF network. Comparisons of the results obtained from the RBF models with those from BP models show that it is feasible to use the RBF network in nondestructive quantitative analysis of the components of drugs.

关键词： Powders Radial basis function networks Clustering algorithms educational institutions Computer science Drugs Spectroscopy educational technology knowledge engineering Artificial neural networks

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CBR and micro-architecture antipatterns based software design improvement

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IFIP TC12 1st International Conference on Artificial Intelligence Applications and Innovations, AIAI 2004

作者： Feng, Tie Zhang, Jiachen Wang, Hongyuan Wang, Xian Institute of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China

ISBN: (纸本)1402081502

This paper presents a Case Based Reasoning (CBR) approach to identifying micro-architecture anti-patterns and replacing them with "good" patterns in order to improve the design of software system. The resulting system design benefits from better flexibility for adapting to future requirement change and expansion. In this approach, both problematic inflexible structures and their corresponding refactoring designs are formally defined and organized in a case base. The identification of anti-patterns is carried out through similarity measurement on class diagrams, sequence diagrams, OO quality metric and semantic constraints. A supporting system CBDIT was developed to aid this approach. © 2004 Springer Science + Business Media, Inc.

关键词： Case based reasoning

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Spatial query preprocessing in distributed GIS

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3rd International Conference on Grid and Cooperative Computing, GCC2004

作者： Wang, Sheng-Sheng Liu, Da-You College of Computer Science and Technology Key Laboratory of Symbolic Computing Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China

ISBN: (纸本)3540235647

This paper focuses on spatial query optimization in distributed GIS. A new qualitative spatial relation model and its consistency problem solution which compose topology, direction, distance and size are proposed. Research integrating the four aspects has not appeared before. A new method to deduce the constraints of spatial query is given, thus saves the query process time in distributed GIS. Finally, The methods and theories are applied to a distributed GIS project, the experiment result is satisfactory. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Topology

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Solving constrained traveling salesman problems by genetic algorithms

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自然科学进展(英文版) 2004年第7期14卷 631-637页

作者： WU Chunguo LIANG Yanchun LEE Heowpueh LU Chun LIN Wuzhong College of Computer Science and Technology Jilin University Key Laboratory for Symbol Computation and Knowledge Engineering Ministry of Education of China Changchun 130012 China Institute of High Performance Computing Singapore 117528 Singapore Institute of High Performance Computing Singapore 117528 Singapore

Three kinds of constrained traveling salesman problems (TSP) arising from application problems, namely the open route TSP, the end-fixed TSP, and the path-constrained TSP, are proposed. The corresponding approaches based on modified genetic algorithms (GA) for solving these constrained TSPs are presented. Numerical experiments demonstrate that the algorithm for the open route TSP shows its advantages when the open route is required, the algorithm for the end-fixed TSP can deal with route optimization with constraint of fixed ends effectively, and the algorithm for the path-constraint could benefit the traffic problems where some cities cannot be visited from each other.

关键词： constrained traveling salesman problem genetic algorithm Hamiltonian path open route fixed end

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A hybrid algorithm for combining forecasting based on AFTER-PSO

A hybrid algorithm for combining forecasting based on AFTER-...

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8th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2004: Trends in Artificial Intelligence

作者： Feng, Xiaoyue Liang, Yanchun Sun, Yanfeng Lee, Heow Pueh Zhou, Chunguang Wang, Yan Key Laboratory of Symbol Computation and Knowledge Engineering Juin University Ministry of Education Changchun 130012 China Institute of High Performance Computing Singapore 117528 Singapore

ISBN: (纸本)3540228179

A novel hybrid algorithm based on the AFTER (Aggregated forecast through exponential re-weighting) and the modified particle swarm optimization (PSO) is proposed. The combining weights in the hybrid algorithm are trained by the modified PSO. The linear constraints are added in the PSO to ensure that the sum of the combining weights is equal to one. Simulated results on the prediction of the stocks data show the effectiveness of the hybrid algorithm. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Algorithms

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Smart home research

Smart home research

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Li Jiang Da-You Liu Bo Yang College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

This paper is a survey for smart home research, from definition to current research status. First we give a definition to smart home, and then describe the smart home elements, typical research projects, smart home ne... 详细信息

ISBN: (纸本)0780384032

关键词： Smart homes Radio frequency Home appliances Home automation Protocols Artificial intelligence Intelligent control Manufacturing Power supplies Computerized monitoring

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User-association mining based on two-stage count

User-association mining based on two-stage count

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ya-Bo Liu Da-You Liu Hong Qi Fang-Ming Gu College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

ISBN: (纸本)0780384032

Both item-associations and user-associations mined from the rating table can be used to make personalized recommendation for the current user in rule-based recommend technique. Mining user-associations is the key for the recommendation based on user-associations. We find that the current user not only can be used to constrain the rule form in user-associations mining process, but also can be used to partition the rating table into two parts in order to accelerate user-associations mining. It is first proved that user-associations about the current user mined from the whole rating table are contained in those mined only from the data set that contain the current user's rating. Then, a user-association mining frame based on two-stage count called TSCF is proposed. TSCF frame can be implemented by using existing algorithms for mining association rules. And an algorithm TSCF-CL for mining user-associations is implemented by using the concept lattice. Last the performance comparison with ASARM algorithm shows that TSCF-CL can reach better time capacity.

关键词： Data mining Association rules Recommender systems Lattices Acceleration Filtering Computer science educational technology Laboratories knowledge engineering

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