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Quadrilateral Interval Type-2 Fuzzy Regression Analysis for Data Outlier Detection
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-08-21
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This paper presents a fuzzy regression analysis method based on a general quadrilateral interval type-2 fuzzy numbers, regarding the data outlier detection.
The Euclidean distance for the general quadrilateral interval type-2 fuzzy numbers is provided.
In the sense of Euclidean distance, some parameter estimation laws of the type-2 fuzzy linear regression model are designed.
Then, the data outlier detection-oriented parameter estimation method is proposed using the data deletion-based type-2 fuzzy regression model.
Moreover, based on the fuzzy regression model, by using the root mean squared error method, an impact evaluation rule is designed for detecting data outlier.
An example is finally provided to validate the presented methods.
American Psychological Association (APA)
Gao, Pingping& Gao, Yabin. 2019. Quadrilateral Interval Type-2 Fuzzy Regression Analysis for Data Outlier Detection. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1195837
Modern Language Association (MLA)
Gao, Pingping& Gao, Yabin. Quadrilateral Interval Type-2 Fuzzy Regression Analysis for Data Outlier Detection. Mathematical Problems in Engineering No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1195837
American Medical Association (AMA)
Gao, Pingping& Gao, Yabin. Quadrilateral Interval Type-2 Fuzzy Regression Analysis for Data Outlier Detection. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1195837
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195837