Human health effects of air pollution, Environmental Pollution, vol.151, issue.2, pp.362-367, 2008. ,
DOI : 10.1016/j.envpol.2007.06.012
Effects of sulfur dioxide derivatives on expression of oncogenes and tumor suppressor genes in human bronchial epithelial cells, Food and Chemical Toxicology, vol.47, issue.4, pp.734-744, 2009. ,
DOI : 10.1016/j.fct.2009.01.005
A nonlinear regression model estimating single source concentrations of primary and secondarily formed PM2, Atmos. Environ, vol.5, issue.45, pp.3758-3767, 2011. ,
Small-Particle Pollution Modeling Using Fuzzy Approaches, Simulation and Modeling Methodologies, Technologies and Applications , Advances in Intelligent Systems and Computing, pp.239-252, 2014. ,
DOI : 10.1007/978-3-319-03581-9_17
Prediction methods and techniques for PM2.5 concentration in urban environment (in Romanian) Methods to assess the effects of air pollution with particulate matter on children's health, pp.387-428, 2014. ,
An empirical relationship between PM2.5 and aerosol optical depth in Delhi Metropolitan, Atmospheric Environment, vol.41, issue.21, pp.4492-4503, 2007. ,
DOI : 10.1016/j.atmosenv.2007.01.046
A neural network-based approach for the prediction of urban SO2 concentrations in the Istanbul Metropolitan Area, Inter, J. Environ. Pol, vol.40, pp.301-321, 2010. ,
Multiple regression, ANN (RBF, MLP) and ANFIS models for prediction of swell potential of clayey soils, Expert Systems with Appl, pp.5958-5966, 2011. ,
Fuzzy neural identification and forecasting techniques to process experimental urban air pollution data, Neural Networks, vol.16, issue.3-4, pp.493-506, 2003. ,
DOI : 10.1016/S0893-6080(03)00019-4
Adaptive neuro-fuzzy based modelling for prediction of air pollution daily levels in city of Zonguldak, Chemosphere, vol.63, issue.9, pp.1575-1582, 2006. ,
DOI : 10.1016/j.chemosphere.2005.08.070
Prediction of daily air pollution using wavelet decomposition and adaptive-network-based fuzzy inference system, International Journal of Environmental Sciences, vol.2, issue.1, pp.185-196, 2011. ,
Neural networks. A comprehensive foundation, 1999. ,
Approximation capabilities of multilayer feedforward networks, Neural Networks, vol.4, issue.2, pp.251-257, 1991. ,
DOI : 10.1016/0893-6080(91)90009-T
Forecasting air pollutant indicator levels with geographic models 3 days in advance using neural networks, Expert Systems with Appl, pp.7986-7992, 2010. ,
Forecasting PM10 in metropolitan areas: Efficacy of neural networks, PM10 in metropolitan areas. Efficacy of neural networks, pp.62-67, 2012. ,
DOI : 10.1016/j.envpol.2011.12.018
Artificial neural networks forecasting of PM2.5 pollution using air mass trajectory based geographic model and wavelet transformation, Atmospheric Environment, vol.107, pp.118-128, 2015. ,
DOI : 10.1016/j.atmosenv.2015.02.030
A comparative study of computational intelligence techniques applied to PM2.5 air pollution forecasting, 2016 6th International Conference on Computers Communications and Control (ICCCC), pp.103-108, 2016. ,
DOI : 10.1109/ICCCC.2016.7496746