Abstract
After having examined the classification approaches to reliability problems in the previous two chapters, we will be concerned herein with the applicability of function approximation methods, with special regard to Neural Networks and Support Vector Machines. Three kinds of networks are of interest in this respect: Multi-Layer Perceptrons, Radial Basis Function Networks and Networks with Time-Dependent connections. The use of Support Vector Machines for regression purposes is based on the extension of the method to non-perfectly separable classes.
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© 2004 Springer-Verlag Berlin Heidelberg
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Hurtado, J.E. (2004). Regression Methods. In: Structural Reliability. Lecture Notes in Applied and Computational Mechanics, vol 17. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-40987-8_6
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DOI: https://doi.org/10.1007/978-3-540-40987-8_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-53576-5
Online ISBN: 978-3-540-40987-8
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