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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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Approximated non-tensor pre-wavelets neural network based on compound training algorithm

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Journal of Information and computational Science 2005年第4期2卷 715-722页

作者： Li, Ying Deng, Zhidong Zou, Xi Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing 100084 China Key Laboratory of Symbol Computation and Knowledge Engineering College of Computer Science and Technology Jilin University Changchun 130021 China Institute of Mathematics Jilin University Changchun 130021 China

In this paper, we propose a new supervised compound learning algorithm for training our constructed approximated bivariate non-tensor product adaptive pre-wavelet neural network (APWNN). On the one hand, the linear weights of APWNN are trained by the self-adaptive learning rate method. On the other hand an extended Kalman filter method is used to update the nonlinear parameters such as dilation parameters and translation parameters. Additionally we demonstrate the efficiency of our proposed method through a concrete example of function approximation.

关键词： Neural networks

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Using spatial clustering in precision agriculture

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Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology 2005年第SUPPL. 4期37卷 31-34页

作者： Wang, Sheng-Sheng Liu, Da-You Liu, Jie Wang, Xin-Ying Key Laboratory of Symbolic Computing and Knowledge Engineering College of Computer Science and Technology Jilin University Changchun 130012 China

There are lots of data with multidimensional attributes and spatial position information in precision agriculture applications. Based on the high dimensional spatial clustering algorithm, the agriculture breed partition method is proposed and applied in Chinese national 863 project. The data mining algorithm is performed in this way: cluster the multidimensional attributes first, then cluster the spatial position information using the former attributes clustering results. Experiments show that the two-phases clustering method is prior to the traditional single-phase clustering method. According to the clustering results, one will decide the region belongs to what kind of soil, select the breeds and the field managements.

关键词： Data mining

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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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Optimal partition algorithm of RBF neural network and its applications to stock price prediction

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Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence 2005年第3期18卷 374-379页

作者： Sun, Yan-Feng Liang, Yan-Chun Zhang, Wen-Li Lu, Ying-Hua Key Laboratory for Symbol Computation and Knowledge Engineering College of Computer Science and Technology Jilin University Changchun 130012 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Department of Computer Science Northeast Normal University Changchun 130024 China

The optimal partition algorithm (OPA) is applied to the training of parameters in the radial basis function (RBF) neural network. The appropriate modification for the OPA is performed according to the characteristics of the RBF neural network. The approach for determining the centers and widths of the clustering is added in the modified OPA and applied to choose the centers and widths of the neural network. A method for adjusting the structure of the neural network dynamically is presented by using the difference of the objective functions of the clustering. Thus it is realized to select the number of the hidden nodes adaptively. Simulation results of the stock price prediction demonstrate the effectiveness of the proposed approach. Comparisons with traditional algorithms show that the proposed OPA method possesses obvious advantages in the precision of forecasting, generalization, and forecasting trends. Simulations also show that the algorithm combining the OPA with the orthogonal least squares (OLS) possesses more superior performance in the rightness of forecasting trends.

关键词： Optimal partition algorithm (OPA) Ordered sample Radial basis function (RBF) neural network Stock price prediction

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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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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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