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检索条件"机构=Key Lab.In Machine Learning and Computational Intelligence"

共 88 条记录，以下是21-30 订阅

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Updating Approximations of VPRS Model based on Dominance Relations

Updating Approximations of VPRS Model based on Dominance Rel...

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作者： Jiajia HOU Yan LI Yan ZHAN Liang WANG Key Lab.In Machine Learning and Computational Intelligence College of Mathematics and Computer ScienceHebei University

In real world problems, the collected data vary from time to time, and therefore, the approximations of a concept by a variable precision rough set model(VPRS) should be correspondingly updated. This paper focuses on developing incremental method to update set approximations of VPRS based on dominance relations. Under dynamic environments where an object is inserted or deleted, we present the updating principles and then develop the incremental method for updating approximation sets. The related theoretical results are presented with proofs, and illustrative examples are also given to support the effectiveness of the proposed method.

关键词： Variable Precision Rough Set Dominance Relation Set Approximation Dynamic Information Systems Incremental Update

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A Core Set Weighted Support Vector machines

A Core Set Weighted Support Vector Machines

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作者： Shuxia LU Limin LI Key Lab.In Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University

Classification for large datasets is a classical problem in machine learning. In this paper, we focus on effevtive classification algorithm for large datasets and imbalanced datasets. First, to deal with imbalanced dataset, we define the weight according to the size of positive and negative dataset. Then, a fast learning algorithm on large datasets called a core set weighted support vector machines(CSWSVM) is proposed. In the proposed approach, the corresponding core set(CS) can be solved by employing the core vector machine(CVM) or generalized CVM(GCVM), and then the weighted support vector machines(WSVM) can be used to implement classification for imbalanced datasets. Experimental results on UCI and USPS datasets demonstrate that the proposed method is effective.

关键词： core vector machine weight support vector machine core set

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A Multi-task Pathfinding Method Based on CBR and Kd-tree

A Multi-task Pathfinding Method Based on CBR and Kd-tree

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作者： Yan Li Sen Liang Lanming Su Jiacheng He Key Lab.In Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University

Pathfinding is a typical task in many computer games, and its performance will affect the quality of game AI. In order to enhance the efficiency of multi-task pathfinding, case-based reasoning has been introduced in traditional A* algorithm, called the CBMT method. The method needs to select representative paths which can cover the whole map to build a compact case base, which is difficult in large maps. Besides, repeatedly searching for similar cases for each pathfinding task would be a time consuming process. To address these problems, we provide a kd-tree case storage structure and case retrieval mechanical in the CBMT method. The pre-stored cases(previously found paths) are generated randomly and incrementally. The original flat storage structure of the cases is changed into the kd-tree structure. Since the searching space can be reduced by branch pruning in case retrieval, the pathfinding efficiency has been improved obviously, and the number of searched nodes is also reduced.

关键词： Multi-task Pathfinding Case-based Reasoning Kd-tree Nearest-neighbors Search Algorithm A

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A Rough Set Model Based on Extended Dominance Relations

A Rough Set Model Based on Extended Dominance Relations

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作者： Yan LI Shuai SUN Yongfei JIN Yan ZHAN Key Lab.In Machine Learning and Computational Intelligence College of Mathematics and Information Science Hebei University

Dominance relation rough set approach(DRSA) is a useful mathematical tool to deal with preference-ordered data. The main idea is using dominance relations to replace equivalent relations in classical rough set theory. However, the definition of conventional dominance relation is very strict which may limit its application to information systems with relative large number of attributes. In this paper, we relax the conditions in the definition of dominance relation and introduce the concept of extended dominance relation. The proprieties of this new concept are also discussed and it is found that all the properties of classical dominance relation are still satisfied.

关键词： Rough Set Information System Dominance Relation DRSA Extended Dominance Relation

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Case-based multi-task pathfinding algorithm

Case-based multi-task pathfinding algorithm

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2012 International Conference on machine learning and Cybernetics, ICMLC 2012

作者： Li, Yan Su, Lan-Ming He, Qiang Key Lab. in Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 Hebei Province China

ISBN: (纸本)9781467314855

Pathfinding is an important task in computer games, where the algorithm efficiency is the key issue. In this paper, we introduce case-based reasoning method in the process of A* algorithm in multi-task pathfinding. Firstly, we save some typical paths as cases. When a new task is coming, it no longer uses A* to find a path from scratch, but firstly computes the similarity of the new task and the stored cases to decide whether to go along the previous found paths or not. A solution to the new task will be obtained after adapting to the found similar case(s). Obviously, this memory-based pathfinding can reduce the search time at the cost of using more memory to store found paths as cases. Through experimental results, it is demonstrated that, as the number of stored paths is increasing, fewer nodes are needed to be searched during the pathfinding process. © 2012 IEEE.

关键词： Case based reasoning

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PSO-based method for learning similarity measure of nominal features

PSO-based method for learning similarity measure of nominal ...

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International Conference on machine learning and Cybernetics

作者： Li, Yan Zhang, Xiu-Li Key Lab. in Machine Learning and Computational Intelligence Faculty of Mathematics and Computer Science Hebei University Baoding 071002 Hebei Province China

ISBN: (纸本)9781424465262

This paper presents a PSO-based method for learning similarity measure of nominal features for case based reasoning classifiers (i.e. CBR classifiers). The symbolic features considered here takes completely unordered values. It has been indicated in [3] that in specific classification task, the similarities between these nominal feature values can not be simply considered as either 0 or 1. A GA-based approach has been developed for learning similarity measure of such feature values. However, when the number of features and feature values become larger, the GA-based algorithm's convergence speed obviously slows down, and the accuracy of classification may be also affected. To address this problem, we propose a PSO-based algorithm for learning similarity measure of nominal features and further describe feature importance through the learned similarity measure. The experimental results show that, using the proposed PSO-based algorithm, the convergence speed is much faster than that of GA-based algorithm and the accuracy is also improved. In addition, we also explain that the feature importance defined through the learned similarities is essentially consistent with that in rough sets, and an illustrative example is finally provided. © 2010 IEEE.

关键词： Particle swarm optimization (PSO)

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Chinese functional chunk identification based on part of speech

Chinese functional chunk identification based on part of spe...

引用

International Conference on Communication Systems and Network Technologies, CSNT 2012

作者： Wang, Cheng-Yan Li, Xin-Fu Tian, Xue-Dong College of Mathematics and Computer Science Hebei University Baoding China Key Lab. in Machine Learning and Computational Intelligence of Hebei Province China

ISBN: (纸本)9780769546926

Chinese functional chunk describes the basic skeleton of the Chinese sentences. It is the important bridge for joining syntax and semantic description, and the Chinese functional chunk identification plays a key role in the field of natural language processing. Identifying the functional chunk is mostly based on methods of rules which come from the syntactic analysis. In this paper, the functional chunk is mainly identified according to the effect of the part of speech in the syntactic analysis. The experimental results show the proposed method works well on the functional chunk identification. © 2012 IEEE.

关键词： Semantics

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Reductions in inconsistent decision systems based on dominance relations

Reductions in inconsistent decision systems based on dominan...

引用

International Conference on machine learning and Cybernetics

作者： Li, Yan Sun, Na-Xin Zhao, Jin Key Lab. In Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 Hebei Province China

ISBN: (纸本)9781424465262

By incorporating domination principle in inconsistent decision systems based on dominance relations, we define the concept of distribution function for a decision system to directly reflect the inconsistent degree of this system. A new type of distribution reduction and maximum distribution reduction are correspondingly introduced. The relationships between these two reductions are discussed, and their judgment theorems are given. In addition, this article also discusses the relations of several existing reductions, including compatible reduction, absolute reduction, and the proposed distribution reduction and maximum distribution reduction. © 2010 IEEE.

关键词： Distribution functions

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An improved research method about the similarity calculation of ontology

An improved research method about the similarity calculation...

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2009 International Conference on Information Engineering and Computer Science, ICIECS 2009

作者： Li, Xin-Fu Yin, Peng Zheng, Mei Key Lab. in Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding China Institute of International Education Yanshan University Qinhuangdao China

ISBN: (纸本)9781424449941

Ontology mapping has been widely used in ontology application, but the similarity calculation becomes a thorny issue in the process of ontology mapping. In this paper, the different elements of ontology are considered. Semantic similarity and concept similarity are integrated to get the ontology similarity. During the similarity calculation of the concept attributes, filter strategy is used to reduce the number of concept attributes, and a method of attributes similarity calculation is proposed. In addition, comprehensive similarity calculation method is given including the semantic and the concept of ontology. The experiment results show that this approach can improve the precision effectively. ©2009 IEEE.

关键词： Ontology

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A survey of the initialization of centers and widths in radial basis function network for classification

A survey of the initialization of centers and widths in radi...

引用

2011 International Conference on machine learning and Cybernetics, ICMLC 2011

作者： Dong, Chun-Ru Chan, Patrick P.K. Ng, Wing W.Y. Yeung, Daniel S. Machine Learning and Cybernetics Research Center School of Computer Science and Engineering South China University of Technology Guangzhou 510006 China Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China

ISBN: (纸本)9781457703065

The radial basis function network (RBFN) has been widely used in various fields such as function regression, pattern recognition, and error detection, etc. However, the structural parameters of RBFN including the number of hidden units, centers vectors, and widths (variances) are one of the most importent issues when training a RBFN, which greatly affect the performance of RBFN. So, the objective of this paper is to construct an elementary survey about this problem. Firstly, the fundamental knowledge and notations of RBFN is introduced. Secondly, we summarize most existing network structure initialization methods for RBFN and categorize them into four goups. Then some typical appraoches for each category are introduced and discussed. The disadvantages and virtues for parts of methods are also introduced. Finally, the paper is concluded with a discussion of current difficulties and possible future directions about RBFN architecture selection. © 2011 IEEE.

关键词： Radial basis function networks

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