Title of article :
Application of Grey System Theory in Rainfall Estimation
Author/Authors :
Darvishi Salookolaei ، Davood - Payame Noor University , Darvishi Salookolaei ، Davood - Payame Noor University , Liu ، Sifeng - Nanjing University of Aeronautics and Astronautics , Liu ، Sifeng - Nanjing University of Aeronautics and Astronautics , Babaei ، Parvin - Payame Noor University , Babaei ، Parvin - Payame Noor University
Abstract :
Considering the fact that Iran is situated in an arid and semi-arid region, rainfall prediction for the management of water resources is very important and necessary. Researchers have proposed various prediction methods that have been utilized in such areas as water and meteorology, especially water resources management. The present study aimed at predicting rainfall amounts using Grey Prediction Methods. It is a novel approach in confrontation with uncertainties in the aquiferous region of Babolrud to serve for the water resources management purposes. Therefore, expressing the concepts of Grey Prediction Method using the collected data, at a 12-year timeframe of 2006 to 2017, rainfall prediction in 2018 to 2022 were also implemented with three methods GM(1,1), DGM(2,1) and Verhulest models. According to the calculated error and the predictive power, GM(1,1) method is better than other models and was placed within the set of good predictions. Also, we predict that in 2027, there might be a drought. According to the small samples and calculations required in this approach, the method is suggested for rainfall prediction in inexact environments. The authors can use fuzzy grey systems to predict the amount of rainfall in uncertaint environments.
Keywords :
Prediction , Grey system , Water resources management , Rainfall amount , Absolute prediction error
Journal title :
control and optimization in applied mathematics (coam)
Journal title :
control and optimization in applied mathematics (coam)