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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Fuzzy Random Regression to Improve Coefficient Determination in Fuzzy Random Environment
verfasst von : Nureize Arbaiy, Hamijah Mohd Rahman
Erschienen in: Recent Advances on Soft Computing and Data Mining
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Determining the coefficient value is important to measure relationship in algebraic expression and to build a mathematical model though it is complex and troublesome. Additionally, providing precise value for the coefficient is difficult when it deals with fuzzy information and the existence of random information increase the complexity of deciding the coefficient. Hence, this paper proposes a fuzzy random regression method to estimate the coefficient values for which statistical data contains simultaneous fuzzy random information. A numerical example illustrates the proposed solution approach whereby coefficient values are successfully deduced from the statistical data and the fuzziness and randomness were treated based on the property of fuzzy random regression. The implementation of the fuzzy random regression method shows the significant capabilities to estimate the coefficient value to further improve the model setting of production planning problem which retain simultaneous uncertainties.