Prediction of Seasonal Temperature Using Soft Computing Techniques: Application in Benevento (Southern Italy) Area
This is an incremental application of existing soft computing methods to a specific, non-maritime region in Italy for local temperature forecasting.
The authors tackled seasonal temperature forecasting in the Benevento area of Southern Italy using Artificial Neural Networks and Genetic Programming, achieving low error rates with Genetic Programming providing an explicit formula for predictions.
In this work two soft computing methods, Artificial Neural Networks and Genetic Programming, are proposed in order to forecast the mean temperature that will occur in future seasons. The area in which the soft computing techniques were applied is that of the surroundings of the town of Benevento, in the south of Italy, having geographic coordinates (lat. 41°07'50"N; long.14°47'13"E). This area is not affected by maritime influences as well as by winds coming from the west. The methods are fed by data recorded in the meteorological stations of Benevento and Castelvenere, located in the hilly area, which characterizes the territory surrounding this city, at 144 m a.s.l. Both the applied methods show low error rates, while the Genetic Programming offers an explicit rule representation (a formula) explaining the prevision. Keywords Seasonal Temperature Forecasting; Soft Computing; Artificial Neural Networks; Genetic Programming; Southern Italy.