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Various credit scoring models have been proposed to estimate credit risk of loan applicants. Recently, the use of artificial immune systems (AIS) in credit problems has been increased. AIS is inspired from natural immune system which has the ability of determining self from non-self. The aim of this study is constructing an AIS-based model to extract fuzzy rules to predict the likelihood of customers...
In order to improve the efficiency of database management and intelligence of database record classification, a classification method of network database record based on fuzzy theory is proposed in this paper. Firstly, an automatic classification frame of database is constructed, and then standard record model and special data record and new record model on fuzzy set are given. By calculating the...
With the development of community service work, community service evaluation becomes more and more important. However, there are not quantitative methods widely accepted for evaluating on community service. Therefore, evaluation on community service is often with a lot of arbitrary and subjective. Using data mining technology based on entropy to mine knowledge information about object classification...
The use of Bayesian Network Classifiers (BCs) combined with the Fuzzy rule model to explain the learned BCs have been previously presented as the BayesFuzzy approach. This paper follows along BayesFuzzy lines of investigation aiming at improving the comprehensibility of a BC model and enhancing BayesFuzzy results by combining new pruning methods. In order to improve BayesFuzzy performance, in addition...
On the basis of most steady state structure of rigid bodies in physical theory, this paper regards data set as physical object, and proposes a dummy digital substantiation viewpoint and some conceptions such as representative data five element groups and model restraint. Then, the algorithm of elasticity based four-point center and borderline (EFCBA) and the algorithm of based on mutual restrict fuzzy...
The core of fuzzy evaluation on the operational performance of e-commerce websites is membership degree transformation. But the existing transformation methods should be questioned, because redundant data in index membership degree is also used to compute object membership degree, which is not useful for object classification. The new algorithm is: using data mining technology based on entropy to...
The natural signal of human such as voice or gesture has been applied to the system for assisting disabled and the elderly people. As an example of such kind of system, the soft remote control system has been developed by HWRS-ERC in KAIST. This system is a vision-based hand gesture recognition system for controlling home appliances such as television, lamp and curtain. One of the most important technologies...
Intrusion detection technique has become increasingly important in the area of network security research. It is innovative that various soft computing approaches have been applied to the intrusion detection field. This paper presents an intelligent intrusion detection system which incorporates several soft computing techniques to implement either misuse or anomaly detection. Genetic algorithm is used...
In an increasingly competitive market, the management of client relationship is becoming a key point for a enterprise to get a success in the competition, client subdivision is a foundation for the enterprise to make a precise marketing strategy and a successful management of client group, based on the development of data mining technology, a fuzzy-C-means(FCM) algorithm model is founded to do the...
Software maintainability means the ease with which a software system or component can be modified to correct faults, improve performance or other attributes, or adapt to a changed environment. For different software maintenance organizations or personnel, there are different concerns on software maintainability. If any one of the factors affecting the maintainability has not been completely resolved,...
The capabilities of distribute data base to store huge amount of data and providing scalability, integrity leads to many of real time databases are stored in distributed nature. In order to apply data mining in real time applications it is important to provide efficient distributed data mining techniques. As a result of the use of online analytical mining (OLAM) technology in new fields of knowledge...
With the growing rate of network attacks, intelligent methods for detecting new attacks have attracted increasing interest. This paper presents an approach incorporating several soft computing techniques to construct a hierarchical neuro-fuzzy inference intrusion detection system which can implement either misuse or anomaly detection. In the proposed system principal component analysis neural network...
Distributed generations have become an important part of electrical generation in many countries and its importance is continuing to increase. The exact models of distributed generations are important for load flow program, stability analyses and other applies in distribution systems. But the absence of basic data results in the difficulty of modeling for distributed generator. Based on the knowledge...
In this paper we explore the use of weights in the generation of fuzzy models. We automatically generate a fuzzy model, using a three-stage methodology: (i) generation of a crisp model from a decision tree, induced from the data, (ii) transformation of the crisp model into a fuzzy one, and (iii) optimization of the fuzzy modelpsilas parameters. Based on this methodology, the generated fuzzy model...
The use of natural language rules that are able to handle vague and, possibly, even contradicting knowledge in order to model formal dependences is an intriguing idea. Fuzzy if-then rules have been proposed as classification methods that can easily be defined and interpreted by humans or built automatically by learning algorithms. This paper gives an intuitive insight into the properties and the behavior...
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