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Inventi Impact: Fuzzy Systems

Articles

  • Inventi:efs/30320/19
    Quadrilateral Interval Type-2 Fuzzy Regression Analysis for Data Outlier Detection
    Research 2020 : January - March
    Pingping Gao, Yabin Gao

    This paper presents a fuzzy regression analysis method based on a general quadrilateral interval type-2 fuzzy numbers, regarding\nthe data outlier detection. The Euclidean distance for the general quadrilateral interval type-2 fuzzy numbers is provided. In the\nsense of Euclidean distance, some parameter estimation laws of the type-2 fuzzy linear regression model are designed. Then, the\ndata outlier detection-oriented parameter estimation method is proposed using the data deletion-based type-2 fuzzy regression\nmodel. Moreover, based on the fuzzy regression model, by using the root mean squared error method, an impact evaluation rule is\ndesigned for detecting data outlier. An example is finally provided to validate the presented methods.

    How to Cite this Article
    Attribution/ CC Compliant Citation: Gao, Pingping, and Yabin\nGao. \"Quadrilateral Interval Type-2 Fuzzy Regression\nAnalysis for Data Outlier Detection.\" Mathematical Problems\nin Engineering 2019 (2019).\nhttps://doi.org/10.1155/2019/4914593\nhttp://creativecommons.org/licenses/by/4.0/\n\nSome formatting elements, header, footer, logos, dates and\npagination were modified while adapting this article.
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