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The application of intelligent optimization algorithm in data mining has become widespread already. However, it's still a brand new research area in the application of Ant Colony Algorithm(ACA) in data mining. This paper thus proposes a fuzzy data mining algorithm which is based on MAX-MIN Ant System(MMAS). In this algorithm, the membership functions which are extracted from the classification rule...
In this paper, we propose a pre-processing technique to improve existing string similarity join algorithms using fuzzy clustering. Our approach first identifies groups of related attributes and then, using this information, we apply existing string similarity join algorithms on these attributes. To identify the clustered attributes we use fuzzy techniques. This approach can be applied to the integration...
The problem of fuzzy pattern recognition based on eigenvector is often met with in computer measurement and control system. Both the object to be identified and the standard pattern stored in the database have a certain degree of uncertainty because errors are inevitable in the process of eigenvector extraction. The problem of fuzzy pattern recognition can be turned into the problem of calculating...
With the aim to improve the KDD process model and achieve the double bases(database and knowledge base) cooperating mechanism, the paper proposed one RBFCM based maintenance coordinator algorithm, which used RBFCM, a soft computing methodology, representing knowledge and inference in order to maintain in time knowledge base harmonizing with the database. On the one hand, maintenance coordinator algorithm...
Humans frequently use a ldquodivide and conquerrdquo strategy to understand large volumes of data, by grouping similar items into progressively finer categories which form a conceptual hierarchy. Typically, such categories do not have crisp definitions but can be modelled by fuzzy set theory, allowing computers to represent and reason about sets of objects in a way that reflects the human interpretation...
The conceptual formalisms supported by typical ontologies may be not sufficient for handling imprecise information commonly found in many application domains. Fuzzy ontologies are developed to overcome this problem. The implementation, inference and query of fuzzy ontologies gain more attention in recent years. This paper addresses fuzzy ontology implementation and query answering on databases. We...
With the development of e-commerce and internet, the retrieval and reuse methodology of a great deal of faults diagnosis and treatment case knowledge in databases of remote center is a key technology in remote diagnosis and e-maintenance. In this article, firstly, the basic method and shortcoming of retrieval mechanism of CBR system is analyzed. The Manhattan distance and fuzzy method based similarity...
The common vulnerability scoring system (CVSS) provides an open, standardized method for rating vulnerabilities. CVSS provides base-level metrics for vulnerability classification that can be used with other strategies such as intrusion detection classification to form a complete diagnostic system. This emphasizes focus on defining and representing the various strategies that can be employed to provide...
In view of design characters of CCBII brake, a state monitor system based on multi-hierarchy evaluation architecture and fuzzy evaluation method is given. Block diagram of brake state monitor system is given, and design features and functions of each part are described, design methods of factor set, safety degree set and itpsilas criterion in multi-hierarchy evaluation system are discussed. Key points...
In the case-based reasoning (CBR) system, the weight determination of cases characters plays a great role in the process of case retrieval, case rewriting and case saving. The fuzzy comprehensive evaluation is proposed to determine the weights of cases characters in CBR system. Taking the high-speed cutting database system for example, the weighting factors affecting the high-speed cutting parameter...
When individual classifiers are combined appropriately, we usually obtain a better performance in terms of classification precision. Multi-classifiers are the result of combining several individual classifiers. In this work we propose and compare various combination methods to obtain the final decision of the multi-classifier based on a ldquoforestrdquo of randomly generated fuzzy decision trees,...
We discuss the structural properties of Klein four-groups and the factor groups of Klein four-groups formed over particular collections of fuzzy propositions and their fuzzy normal forms. We consider three alternative collections of operators, namely, (i) max, min; (ii) probabilistic sum, product; (iii) bold union, bold intersection. We show that these structural properties (i) provide a base for...
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