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Erschienen in:
2012 | OriginalPaper | Buchkapitel
A New Fuzzy Linear Regression Model for Least Square Estimate
verfasst von : Xiuli Nong
Erschienen in: Information and Business Intelligence
Verlag: Springer Berlin Heidelberg
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In many research, we have data from fuzzy or language, such as "about 10 ’, and is more than 10 ’, heavy" moderate ", etc. In order to describe the relationship between variables, not run in the same process, tanoak [2] was established on the basis of fuzzy regression model based on the traditional some linear regression model. In addition, in the measurement process, error is random. Cause measurement errors caused by fuzzy random and fuzzy system of two kinds of uncertainty, coexist in a regression analysis. Therefore, Nather [3] and [4], red and Huang Wang as linear estimation theory development of regression model parameters of fuzzy random data. In this paper, we discussed the fuzzy least-square estimation of parameters of fuzzy linear regression model and the some asymptotic character. It is not hard to find, if we use data on crisp, instead of a fuzzy observation, we estimate of classic estimated to reduce.