Post-Evaluation Base on the Wavelet the Particle Swarm Optimization BP Neural Network Evidence
Li Chen · 2009
Post-evaluation of projects is an important research field. In this paper, we applied the wavelet the Particle Swarm Optimization (PSO) BP Neural Network evidence to evaluate a project. The research based on the PSO- BP Neural Network evidence theory has not been able to consider the problem of noise data. But the evidence synthesis method of combining particle swarm optimization and neutral network has the very strong sensitivity to the noise data. In this paper, we proposed a solution to overcome this noise data problem using the theory of the wavelet. The simulation of post-evaluation based on the wavelet PSO-BP Neural Network evidence for the projects showed that the method is effective and reasonable. The result is satisfied.