earticle

영어

Proposed a modified Nelder‐Mead simplex
algorithm for training radial basis function neural
networks (RBF‐NN). Traditional simplex algorithm
consists of order, reflect, expand, contract and
shrink operations, and to construct vertices on
the subspace near the constraints. In the
improved simplex algorithm, considered the new
operate method in the feasible fields near the
constrained boundary. This modified method is
simple, accuracy and higher efficiency. Numerical
experiments show that this method is promising
for optimization design of temperature
compensation networks.