Research for breakout prediction system based on support vector regression

摘要

SVM is widely used in the pattern recognition. It shows prediction ability well. For the system nonlinear and complexity of the CCM bonding breakout forecast system nonlinear, complexity, and breakout forecast system based on the least squares support vector machine (LSSVM) is put forward. In forecast system, establish 0–1 more value data window to eliminate the redundant data. The simulation results show that the LSSVM model cans quickly the training sample parameters in the small sample. It shows strong recognition ability, high precision.