Neuro-Fuzzy Air Pollution Forecasting

Forecasting in dynamic systems aims to develop a model that can accurately behave similar to the main system. In problems like Air pollution forecasting, the presence of uncertainties and nonlinearities affects the model's precision. As an index for air pollution, ozone concentration is predicted in this paper using Neuro- Fuzzy models. The results are compared to a previous Fuzzy Logic approach to demonstrate the proposed model's reliability and accuracy.

Keywords:

forecasting , neuro-fuzzy models , air pollution , ozone concentration