检索结果-内蒙古大学图书馆

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Hai-Bin Sun Wen-Hui Li Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun China

In this article, we investigate the problem of preparing qualitative spatial relations before implementing spatial data mining by checking consistency in a constraint network, which includes topological and cardinal directional relations between pairs of spatial objects. We aim to explore potential spatial relations and possible inconsistency among the data of relationships for enforcing the correctness of spatial data mining. This task is carried out through qualitative spatial reasoning method, specifically consistency checking. We try to lay the theoretical foundation for this kind of problem. Instead of using conventional composition tables, we investigate the interactions between topological and cardinal directional relations with the aid of rules. These rules are shown to be sound, i.e. the deductions are logically correct. Based on these rules, an improved constraint propagation algorithm is introduced to enforce the path consistency. An example is presented to show the utility of these rules.

关键词： Cleaning Data mining computational complexity Spatial databases Topology Sun Laboratories Computer networks knowledge engineering Computer science education

来源：评论

学校读者我要写书评

暂无评论

Robust estimation of the fundamental matrix based on an error model

Robust estimation of the fundamental matrix based on an erro...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Hui-Xiang Zhong Yue-Ping Feng Yun-Jie Pang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China

A new method is presented for robustly estimating fundamental matrix from matched points. The method comprises two parts. The first uses a robust technique - the random sample consensus (RANSAC) to discard outliers in an initial set of matched points. It adopts the sampling strategy to generate inliers from the initial set. The second part of the method is an algorithm for computing fundamental matrix, using the output of the RANSAC. This algorithm is based on the consistent fundamental matrix estimation in a quadratic measurement error model. An extended system for determining the estimator is proposed, and an efficient implementation for solving the system - a continuation method is developed. The proposed algorithm avoids solving total eigenvalue problems. Results for both synthetic and real images show the effectiveness of the proposed method.

关键词： Robustness Measurement errors Computer errors Eigenvalues and eigenfunctions Computer vision Layout Educational institutions Computer science Educational technology Laboratories

来源：评论

学校读者我要写书评

暂无评论

Medicine composition concentration analysis based on least square support vector machine

Medicine composition concentration analysis based on least s...

引用

International Conference on Machine Learning and Cybernetics, ICMLC 2005

作者： Guo, Xin-Chen Chen, Zhou-Yi Teng, Li-Rong Wu, Chun-Guo Du, Tian-Bao Lu, Jia-Hui Meng, Qing-Fan Liang, Yan-Chun Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China College of Science NortheastChinaInstituteofElectricPowerEngineering Jilin 132012 China Institute of General Development and Evaluation of Equipment EAAF PLA Beijing 100076 China College of Life Science Jilin University Changchun 130012 China

ISBN: (纸本)078039092X

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. © 2005 IEEE.

关键词： Medicine

来源：评论

学校读者我要写书评

暂无评论

AN IMPROVED BICLUSTERING ALGORITHM AND ITS APPLICATION TO GENE EXPRESSION SPECTRUM ANALYSIS

引用

Genomics, Proteomics & Bioinformatics 2005年第3期3卷 189-193页

作者： Hua Qu Liu-Pu Wang Yan-Chun Liang Chun-Guo Wu College of Software Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China Guangzhou Institute of China Telecom Guangzhou 510630 China College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China Key Laboratory of Information Science and Engineering of the Ministry of Railway/Key Laboratory of Advanced Information Science and Network Technology of Beijing Beijing Jiaotong University Beijing 100044 China.

Cheng and Church algorithm is an important approach in biclustering algorithms. In this paper, the process of the extended space in the second stage of Cheng and Church algorithm is improved and the selections of two important parameters are discussed. The results of the improved algorithm used in the gene expression spectrum analysis show that, compared with Cheng and Church algorithm, the quality of clustering results is enhanced obviously, the mining expression models are better, and the data possess a strong consistency with fluctuation on the condition while the computational time does not increase significantly.

关键词： biclustering algorithm gene expression pedigree analysis Cheng and Church algorithm

来源：评论

学校读者我要写书评

暂无评论

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

Nondestructive quantitative analysis of compound paracetamol...

引用

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

来源：评论

学校读者我要写书评

暂无评论

Incremental algorithm for detecting community structure in dynamic networks

Incremental algorithm for detecting community structure in d...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Bo Yang Da-You Liu Open Symbol Computation and Knowledge Engineering Laboratory of State Education Department Jilin University Changchun China Jilin University Changchun Jilin CN Coll. of Comput. Sci. & Technol. Jilin Univ. Changchun China

Community structure is an important property of networks. Being able to identify communities can provide invaluable help in exploiting and understanding both social and non-social networks. Several algorithms have been developed up till now. However all these algorithms can work well only with small or moderate networks with vertexes of order 10/sup 4/. Additionally, all existing algorithms are off-line and can not work well with highly dynamic networks such as Web, in which Web pages are updated frequently every day. When the already clustered network is updated, the entire network including original and incremental parts has to be recalculated, even only slight changes involved. To address this problem we develop an incremental algorithm which allows for detecting community structure in large-scale and dynamic networks. Based on the community structure it detect previously our algorithm takes little time to reclassify the entire network including both original and incremental parts. Furthermore, our algorithm is faster than most existing algorithms such as Girvan and Newman's algorithm and its improved versions. Also our algorithm can help to visualize these community structures in network and provide a new approach to research the evolving process of dynamic networks.

关键词： Intelligent networks Clustering algorithms Partitioning algorithms Social network services Machine learning algorithms Computer networks Visualization Web sites Biochemistry Educational institutions

来源：评论

学校读者我要写书评

暂无评论

Medicine composition concentration analysis based on least square support vector machine

Medicine composition concentration analysis based on least s...

引用

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

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

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

Nondestructive quantitative analysis of compound paracetamol...

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：