Prediction and Analysis of Micro-regional PM2.5 Concentration Using Kalman-Interpolation Model

摘要

In recent years, the pollution problem of particulate matter concentration, and especially about PM2.5 concentration, is becoming more and more serious, which has attracted many people's attention from all over the world. In this paper, a Kalman prediction model combined with cubic spline interpolation is proposed, which is applied to predict the concentration of PM2.5 in the micro regional environment of campus, and to realize interpolation simulation diagram of concentration of PM2.5 and simulate the spatial distribution of PM2.5. And the experiment data are based on the laboratory which has set up environmental information monitoring system. Since the predicted and actual values of PM2.5 concentration data has been checked by the Wilcoxon signed-rank test. We find that the value of bilateral progressive significance probability was 0.527, which is much greater than the significant level a=0.05. Subsequently, we put Kalman prediction and BP prediction into comparison as well as the SVM prediction. The experimental results show that the absolute error and relative error of Kalman prediction results are small, and the availability of Kalman prediction model of prediction about the PM2.5 concentration is verified. Thus, the Kalman- prediction model has a good effect on the prediction of PM2.5 concentration. In addition, with the combination of Kalman prediction model and the spline interpolation method, the spatial distribution and local pollution characteristics of PM2.5 can be simulated.