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

共 88 条记录，以下是21-30 订阅

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A Fast Algorithm for Computing Dominance Classes

A Fast Algorithm for Computing Dominance Classes

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作者： Yan LI Qun YU Key Lab.Of Machine Learning and Computational Intelligence College of Mathematics and Information Science Hebei University

Traditional rough set theory(TRS) is based on the concept of equivalence relation to define upper and lower approximation sets of a given target concept, and therefore uncertainties in information systems can be represented. By using equivalence relations, TRS only considers whether attribute values are distinguished or not, regardless of the preference information contained in attribute values. Rough sets based on dominance relations effectively solve this problem and can deal with preference-ordered data. In these dominance-based approaches, the computational cost of the dominance classes greatly affects the efficiency of attribute reduction and rule extraction. This paper presents an efficient method of computing dominance classes in an ordered information system by rapidly reducing the search space. Based on the definition of dominance class, the inferior class of an object is gradually removed from the universe with the increase of the attributes in the computation process. Experiments on ten UCI data sets show that the proposed algorithm obviously improves the efficiency of computing dominance classes, especially for large-scale data.

关键词： Rough set dominance class ordered information systems fast algorithm

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Variable-precision Rough Set Approach based on Extended Dominance Relations

Variable-precision Rough Set Approach based on Extended Domi...

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

According to the definition of dominance relation, an object x is said to dominate another object y only when x dominates y on all attributes, which is too strict especially when the number of attributes is large. To cope with this problem, the extended dominance-based rough set model has been developed by introducing a parameter to the concept of traditional dominance relationship in the reported literature. However, in this extended model, the definitions of lower and upper approximations are the same to the traditional model, which may affect the decision making process. In this paper, we introduce the idea of variable precision to the extended dominance rough set model for better fault tolerance ability. The impact of the parameter on decision results with respect to testing accuracy is studied. Finally, an example is given and the experimental results on UCI data are also shown to support the effectiveness of the proposed method.

关键词： Extended dominance relation Variable precision rough set Dominant sets Approximation sets

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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 ...

引用

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...

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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...

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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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MINING THE HOTTEST TOPICS ON CHINESE WEBPAGE BASED ON THE IMPROVED K-MEANS PARTITIONING

MINING THE HOTTEST TOPICS ON CHINESE WEBPAGE BASED ON THE IM...

引用

2009 International Conference on machine learning and Cybernetics(2009机器学习与控制论国际会议)

作者： YU WANG YA-HUI XI LIANG WANG Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Science HebeiUniversity Baoding 071002 China

This paper presents a new method for the mining the hottest topics on Chinese webpage which is based on the improved k-means partitioning algorithm. The dictionary applied to word segmentation is reduced by deleting words which are useless for clustering, and the dictionary tree is created to be applied to word segmentation. Then the speed of word segmentation is improved. Correspondence between words and integers is created by coding words. Then the title is expressed by integer set, and the cost of space and time for clustering is decreased largely. Determining the value of k is a shortcoming of stream data mining based on k-means. By this new method, the value of k is adjusted in clustering. Then both the accuracy and the speed are improved.

关键词： k-means partitioning Data stream Word segmentation Mining the hottest topics

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AN INEXACT REASONING ALGORITHM BASED ON INTERACTION WITH FUZZY RULE MATRIX TRANSFORMATION

AN INEXACT REASONING ALGORITHM BASED ON INTERACTION WITH FUZ...

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2009 International Conference on machine learning and Cybernetics(2009机器学习与控制论国际会议)

作者： AI-XIA CHEN NING LI LI ZHAO HONG-TAO ZHU GUO-FANG ZHANG Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China

This paper presents a reasoning algorithm based on interaction with fuzzy rule matrix transformation, and applies it to completing the patterns. Then the new full patterns will be used in training and synthetic judgment The investigation shows that the method is effective and may be widely used in Reasoning with Incomplete Knowledge.

关键词： Fuzzy measure Interaction Fuzzy integral Fuzzy rule matriz transformation Inezact reasoning algorithm

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SOME PROPERTIES OF OPERATIONS ON TYPE-2 FUZZY SETS

SOME PROPERTIES OF OPERATIONS ON TYPE-2 FUZZY SETS

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2008 International Conference on machine learning and Cybernetics(2008机器学习与控制论国际会议)

作者： SHUO WANG SHU-MING WANG YING LIU Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China

In this study, we study set operations on type-2 fuzzy sets. We first discuss join and meet operations of membership grades of type-2 fuzzy sets under left continuous t-norms and derive distributive law of type-2 fuzzy sets. Then, some properties on compositions of fuzzy relations is discussed. We derived that the distributive laws under union and composition of type-2 fuzzy relations is valid. An example shows the failure of distributive laws under intersection and composition.

关键词： Composition Fuzzy relation Operation Type-2 fuzzy set Triangular norm

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APPLICATION OF INTELLIGENT DECISION SUPPORT TECHNOLOGY IN POWER SYSTEM

APPLICATION OF INTELLIGENT DECISION SUPPORT TECHNOLOGY IN PO...

引用

2009 International Conference on machine learning and Cybernetics(2009机器学习与控制论国际会议)

作者： HAO CHEN YAN ZHAN HAI-YAN LIU Key Lab.of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 China

Distribution network cabling planning is a very complex project This paper proposes the application of intelligent decision support technology in Power System. By adding a module library and the concept of model management systems, Intelligent Power Service System realizes intelligence decision support in the distribution network power cabling planning by using dynamic programming, spatial data mining and decision tree techniques, and has a certain amount of self-learning ability.

关键词： Intelligent Decision Support System Decision tree Power cabling scheme GIS

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