Abstract
In this paper, we present a new support vector neural network inference system (SVNNIS) for regression estimation. The structure of the proposed SVNNIS can be obtained similar to that in the support vector regression (SVR), while the output of the SVNNIS is unbiased compared with the SVR and the weights can be updated by the recursive least square method with forgetting factor. The advantage of this system is its good generalization capability. The simulation result illustrates the effectiveness of the proposed SVNNIS.
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© 2005 International Federation for Information Processing
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Wang, L., Mu, ZC. (2005). A New Support Vector Neural Network Inference System. In: Shi, Z., He, Q. (eds) Intelligent Information Processing II. IIP 2004. IFIP International Federation for Information Processing, vol 163. Springer, Boston, MA. https://doi.org/10.1007/0-387-23152-8_60
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DOI: https://doi.org/10.1007/0-387-23152-8_60
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-23151-8
Online ISBN: 978-0-387-23152-5
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