Environmental ScienceComputer Science

Recursive neural network model for analysis and forecast of PM10 and PM2.5

F. Biancofiore, M. Busilacchio, M. Verdecchia, B. Tomassetti, Eleonora Aruffo, S. Bianco, S. D. Tommaso, C. Colangeli, Gianluigi Rosatelli, P. Carlo

2017.7.1Atmospheric Pollution Research

DOI: 10.1016/j.apr.2016.12.014

tlooto Summary

The comparison between observed and forecasted PM2.5 shows that the neural network is able to forecast the PM 2.5 concentrations even if PM2,5 is not included among the input parameters, compared to the air quality limits for health protection.

Abstract

Abstract is not available.

Citation format

BIANCOFIORE, F., et al. Recursive neural network model for analysis and forecast of PM10 and PM2.5. Atmospheric Pollution Research, 2017, 8: 652–659.