Forecasting Average Monthly Temperature Using Improved Gray Model (Case Study: Climatology Station of Qazvin Airport)

Forecasting Average Monthly Temperature Using Improved Gray Model (Case Study: Climatology Station of Qazvin Airport) Abstract The theory of grey system is used when sufficient information of the community under study is not in hand. The grey forecast model is proper when the information variety is fix and certain. Grey model can apply some additional computations to improve forecasting activities when data is insufficient. Through using improved grey model, the assessment error decreases significantly. This study made use of the mean maximum monthly temperature data for April to September collected by Qazvin climatology station in airport, from 2001 to 2012. The aim was to forecast of the mean maximum monthly temperature for April to September in 2013. The findings revealed that the improved grey model (changeabl estarting point model and metabolism method) can increase the precision of forecasting the mean variable of maximum monthly temperature. Forecasts for April (20.9 versus 21.3 cellcious degree) and June (30.6 vs. 30.9 cellcious degree) had a good accuracy, while August and September's predictions were less trusted. Key words: Forecast, gray model, metabolism, meteorology.