The adaptive particle swarm optimization is used to optimize the parameters of SVM so as to avoid artificial arbitrariness and enhance the forecast accuracy.
The calculation process of the method is independent of size parameters, and it is more stable and faster than the traditional methods based on Lorenz-Mie theory or Debye-series expansion.