Prediction and Analysis of Air Quality Based on FCM and BP Neural Network

摘要

In the paper,we solve the problems of air quality prediction and evaluation. Firstly,the original data of air quality monitoring are classified by fuzzy C means clustering algorithm( FCM); then the BP neural network model to predict the level of air quality is built through the simulation training of data. Experiments show that the model has good generalization ability and strong stability,and the prediction accuracy is higher,which has certain application value.