1. Caselli, M., Trizio, L., de Gennaro, G., & Ielpo, P. (2009). A simple feedforward neural network for the PM10 forecasting: comparison with a radial basis function network and a multivariate linear regression model. Water, Air, & Soil Pollution, 201(1-4), 365–377.
2. Dimitriou, K., Kassomenos, P. A., & Paschalidou, A. K. (2013). Assessing air quality with regards to its effect on human health in the European Union through air quality indices. Ecological Indicators, 27, 108–115.
3. Dunea, D., Oprea, M., & Lungu, E. (2008). Comparing statistical and neural network approaches for urban air pollution time series analysis. In L. Bruzzone (Ed.), MIC ‘08 Proceedings of the 27th IASTED International Conference on Modelling, Identification and Control (pp. 93–98). Anaheim: Acta Press.
4. Dunea, D., Pohoata, A., & Lungu, E. (2011). Fuzzy inference systems for estimation of air quality index. ROMAI Journal, 7(2), 63–70.
5. Dunea, D., Iordache, S., Oprea, M., Savu, T., Pohoata, A., & Lungu, E. (2014). A relational database structure for linking air pollution levels with children’s respiratory illnesses. Bulletin UASVM Agriculture Cluj-Napoca, 71(2), 205–213.