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2016 | OriginalPaper | Chapter

Support Vector Machines in Fuzzy Regression

Authors : Paulina Wieszczy, Przemysław Grzegorzewski

Published in: Challenging Problems and Solutions in Intelligent Systems

Publisher: Springer International Publishing

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Abstract

This paper presents methods of estimating fuzzy regression models based on support vector machines. Starting from the approaches known from the literature and dedicated to triangular fuzzy numbers and based on linear and quadratic loss, a new method applying loss function based on the Trutschnig distance is proposed. Furthermore, a generalization of those models for fuzzy numbers with trapezoidal membership function is given. Finally, the proposed models are illustrated and compared in the examples and some of their properties are discussed.

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Title: Support Vector Machines in Fuzzy Regression
Authors: Paulina Wieszczy
Przemysław Grzegorzewski
Publisher: Springer International Publishing
Book: Challenging Problems and Solutions in Intelligent Systems
Print ISBN: 978-3-319-30164-8

Electronic ISBN: 978-3-319-30165-5

Copyright Year: 2016
DOI: https://doi.org/10.1007/978-3-319-30165-5_6

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