Fuzzy regression based on asymmetric support vector machines

DOI10.1016/j.amc.2006.03.046zbMath1113.62084OpenAlexW1991421040MaRDI QIDQ861087

Pao-Ta Yu, Chih-Chia Yao

Publication date: 9 January 2007

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2006.03.046

zbMATH Keywords

fuzzy regressionnonlinearasymmetricSVMsorthogonal vector

Mathematics Subject Classification ID

Linear inference, regression (62J99) General nonlinear regression (62J02) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (5)

A nonlinear modeling with linear fuzzy numbers for replicated response measures ⋮ Least-squares approach to regression modeling in full interval-valued fuzzy environment ⋮ A weighted goal programming approach to estimate the linear regression model in full quasi type-2 fuzzy environment ⋮ Extended support vector interval regression networks for interval input-output data ⋮ Real-time fuzzy regression analysis: a convex hull approach

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• Fuzzy regression using asymmetric fuzzy coefficients and fuzzified neural networks

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