BP neural network application in C2C e-commerce trust evaluation based on particle swarm optimization

The rapid development of Internet technology has also driven the development of electronic commerce, but electronic commerce because of information asymmetry and prone to crisis of trust. So the particle swarm optimization BP neural network model is applied to C2C e-commerce degree evaluation of trust, By using PSO algorithm to optimize the BP neural network´s connection weight values and threshold values, it can give full play to the global optimization ability of the PSO and BP algorithm local search advantage as well as overcome the randomness problem of BP neural network weight values. Now the instance verification results of the C2C e-commerce trust evaluation show that the model has two advantages: the first is the convergence speed is very fast in the operation process and the second is the computation results have a higher precision; and the results also show that the model can accurately evaluate the trust dgree in C2C ecommerce.