Research of Chinese word segmentation based on neural network and particle swarm optimization

For the research of Chinese word segmentation, the BP algorithm model has a lot of defects such as low convergent velocity, easily falling into local minimum, low velocity and efficiency. In this paper, we proposed a new particle swarm neural network algorithm (NPSO-BP), and used it in Chinese word segmentation. The results show that the speed of the segmentation algorithm is obviously faster than the traditional BP neural networks. It has high accuracy and high convergent velocity characteristics.