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To estimate the parameters of fuzzy linear regression model with crisp input and fuzzy output, we construct a method based on minimizing the least square errors, and propose some relative conclusions including normal equations, minimum solution, unique solution and their analytical expressions of fuzzy parameters. Finally, one numerical example is used to illustrate our proposed methods reasonable.
In the problem of multiple criteria decision making, there are situations in which information is incomplete or imprecise or views that are subjective or endowed with linguistic characteristics creating a "fuzzy" decision making environment, some index can't be expressed by certain number, just only expressed by linguistic words, under this situation, we must use fuzzy decision making method...
Residuated lattice is an important non-classical logic algebra, and L-fuzzy rough set based on residuated lattice can describe the information with incompleteness, fuzziness and uncomparativity in information system. In this paper, the properties of L-fuzzy rough sets based on residuated lattice are given as the expansion of ref.
In a complex system, schemes are affected by lots of factors. The evaluation must take all the factors into account. The nature of the factors are fuzzy and grey, this paper apply grey relational analysis and entropy weights into fuzzy design theory, and solve the problem of three levels structure fuzzy comprehensive evaluation. A practical example of torpedo is showed to prove the validity of the...
In this paper the traffic congestion recognition method is studied deeply based on the pattern recognition technology which is well integrates the fuzziness and randomness of linguistic concepts in a unified way, and makes the transforms between qualitative concepts and their quantitative expressions much easier and interchangeable. Moreover, the feasibility and effectiveness of that new method which...
Clustering is one of the important means of Intrusion detection. In order to overcome the disadvantages of fuzzy C-means algorithm, this paper presents a kind of improved fuzzy C-means algorithm (IFCM for short). IFCM algorithm reduces the infection of isolated point by means of weighting the degree of membership for objects to be clustered, and avoids the subjectivity in choosing the number of clustering...
This paper proposes an improved Grey-Markov forecasting dynamic method based on unbiased grey system theory and fuzzy classification. The new forecasting method is named unbiased Grey-fuzzy-Markov Chain method, which can take advantage of the prediction power of conventional Grey-Markov forecasting method and at the same time eliminate grey bias and improve anti-jamming performance. As an example,...
This paper introduces an image segmentation algorithm of weighted with neighborhood gray difference fuzzy c-means clustering (WFCM) and experiments with the samples on two-dimensional histogram between the original image and its median filter image. Experimental results demonstrate that this scheme can not only effectively segment the low contrast object, but also reduce the noise from the background.
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