-
Artificial Intelligence and Computational Intelligence, International Conference, AICI 2009, Shanghai, China, November 7-8, 2009. Proceedings; 01/2009
-
[show abstract]
[hide abstract]
ABSTRACT: In order to apply the classical rough set theory in the incomplete information system, equivalence relation has been extended, such as rough set model based on set pair connection degree. But as the binary relation defined in this model has some limitations, inconsistent problems will happen in the process of decision making and when null values are too many the performance is not desirable. In this paper, the reason of these limitations generation is analyzed, and in view of these limitations, a new binary relation based on set pair connection degree, called generalized set pair similarity relation, is proposed. Based on this a more generalized rough set model is presented. Finally, the compare of the generalized rough set mode with some existing extension of rough set models is given. By an example, it is demonstrated that the new model is simpler and more effective when processing incomplete information system.
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on; 09/2007
-
[show abstract]
[hide abstract]
ABSTRACT: Concept hierarchies are important in many generalized data mining applications, such as multiple-level fuzzy association rule mining. Usually concept hierarchies are given by domain experts. However, it is extremely difficult and time-consuming for human experts to discover concepts and construct concept hierarchies from the domain. In literature, several representations of concept hierarchy are possible, for example tree, lattice, table, linked list, arbitrary graph etc. In this paper, we apply quotient space model to representing concept hierarchies. In contrast to others, the representation model is much more extensible and compatible. The results indicate that this technique can improve the efficiency of performing the generalization and specialization operation in concept hierarchies.
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on; 09/2007
-
[show abstract]
[hide abstract]
ABSTRACT: This paper describes a training method based on decision tree for shooting skill of the agents in the RoboCup simulator league. The training method enables an agent to find the best shooting point and shooting time to get the maximum probability of scoring.
Machine Learning and Cybernetics, 2003 International Conference on; 12/2003
-
[show abstract]
[hide abstract]
ABSTRACT: In this paper, a new type information retrieval scheme is designed using rough set theory and fuzzy set knowledge. A new information retrieval method is advanced. The architecture of the system and its key algorithms are given and their time complexities are analyzed. Main characteristic of the research achievement is that the orders of the retrieval algorithm, which is O(log<sub>2</sub> M), only relates to the number of index words but does not increase with the augment of the number of documents. Analysis of the method shows our scheme is efficient.
Machine Learning and Cybernetics, 2003 International Conference on; 12/2003
-
[show abstract]
[hide abstract]
ABSTRACT: Case-based reasoning systems solve new problems by using previous problem solving experiences stored as cases in a case base. In recent years the integrated methods of case-based reasoning became an increasingly important research issue for the case-based reasoning community. In this paper we research the integrated case-based reasoning method based on rule-based reasoning, or induction learning technique so as to heighten the efficiency of problem-solving of case-based reasoning. We also utilize genetic algorithm in an integrated case-based reasoning approach. The experiments show that the new model of integrated case-based reasoning has got a better accuracy rate of classification.
Machine Learning and Cybernetics, 2003 International Conference on; 12/2003
-
[show abstract]
[hide abstract]
ABSTRACT: We introduce the concepts of a geographic information system, and study in detail spatial database and rough set theory. A set of algorithms of data reduction and data mining about attribute data in a spatial database is given. Finally, an example applying the theory to practice is presented, which verifies the feasibility of the algorithms.
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on; 02/2002
-
[show abstract]
[hide abstract]
ABSTRACT: An important factor that plays a major role in determining the performance of a case-based system is the complexity and the accuracy of the case retrieval phase. The nearest neighbor search, knowledge-based method and the inductive approach all suffer from serious drawbacks. This paper examines the possibility of using neural networks as a method of retrieval in such case-based systems. A simple efficient case-based system structure is constructed with neural networks. Also, some algorithms are proposed and tested. The application results show that the approach is efficient.
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on; 02/2002
