%0 Journal Article %A S. Esfandeh and M. Sedighizadeh %D 2011 %J International Journal of Environmental and Ecological Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 50, 2011 %T Meteorological Data Study and Forecasting Using Particle Swarm Optimization Algorithm %U https://publications.waset.org/pdf/838 %V 50 %X Weather systems use enormously complex combinations of numerical tools for study and forecasting. Unfortunately, due to phenomena in the world climate, such as the greenhouse effect, classical models may become insufficient mostly because they lack adaptation. Therefore, the weather forecast problem is matched for heuristic approaches, such as Evolutionary Algorithms. Experimentation with heuristic methods like Particle Swarm Optimization (PSO) algorithm can lead to the development of new insights or promising models that can be fine tuned with more focused techniques. This paper describes a PSO approach for analysis and prediction of data and provides experimental results of the aforementioned method on realworld meteorological time series. %P 108 - 110