Application of neural network based on particle swarm algorithm for the prediction of oil quality
基于粒子群优化算法的神经网络在油品质量预测中的应用

PSO(particle swarm optimization) algorithm is a kind of stochastic global optimization based on swarm intelligence. Through the interaction of particles, PSO searches the solution space intelligently and finds out the best solution. The advantage of PSO is that it is easy to operate and to achieve. A model integrating PSO and NN (neural network) was established in this paper, which takes full use of the global optimization of PSO and local accurate searching of BP. The example of oil quality prediction shows that PSONN is more efficient and has good generalization.