\`x^2+y_1+z_12^34\`
Advanced Search
Article Contents
Article Contents

Knot-optimizing spline networks (KOSNETS) for nonparametric regression

Abstract Related Papers Cited by
  • In this paper we present a novel method for short term forecast of time series based on Knot-Optimizing Spline Networks (KOSNETS). The time series is first approximated by a nonlinear recurrent system. The resulting recurrent system is then approximated by feedforward $B$-spline networks, yielding a nonlinear optimization problem. In this optimization problem, both the knot points and the coefficients of the $B$-splines are decision variables so that the solution to the problem has both optimal coefficients and partition points. To demonstrate the usefulness and accuracy of the method, numerical simulations and tests using various model and real time series are performed. The numerical simulation results are compared with those from a well-known regression method, MARS. The comparison shows that our method outperforms MARS for nonlinear problems.
    Mathematics Subject Classification: Primary: 62M10, 65K05; Secondary: 41A15, 37M10.

    Citation:

    \begin{equation} \\ \end{equation}
  • 加载中
SHARE

Article Metrics

HTML views() PDF downloads(100) Cited by(0)

Access History

Other Articles By Authors

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return