Air Quality Index Prediction Based on Improved PSO-BP

Abstract

For air quality index prediction problem, this paper puts forward the optimization based on improved PSO - BP algorithm, the method using particle swarm weights and threshold of BP neural network is optimized, and the update each particle’s position and speed of the weight of adaptive adjustment strategy, to balance the global optimization and local optimization ability, and it has been verified by experiment that the improved PSO - BP neural network model is compared with PSO -BP and GA - BP and BP on prediction accuracy improved.