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In this paper, the fundamental idea of Linguistic Models (LM) introduced by Pedrycz is followed and their genetically oriented design framework is developed. The LM is designed by the use of fuzzy granulation realized via Context-based Fuzzy C-Means (CFCM) clustering. This clustering technique builds information granules in the form of fuzzy sets and develops clusters by preserving the homogeneity...
A new methodology to learn descriptive linguistic Fuzzy Rule-based System Knowledge Bases from examples based on the combination of fuzzy clustering and evolutionary simultaneous rule selection and membership functions tuning is presented in this work. Fuzzy clustering is used to achieve a preliminary description of the data, in other words to obtain information on the definition of the linguistic...
In this paper, computational verb theory (CVT) is applied to the analysis of stock market data. By using CVT, stock market data are clustered into different categories and represented by typical curves for each category. In this paper, researches on the market data samples from Shanghai Stock Exchange in March 2010 are reported. Firstly, MATLAB programs are used to preprocess the stock data. The preprocess...
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