Investigating the relationship between drought parameters and food security using data mining methods (Case study: Alborz province)

Nowadays, due to the increase in population and the ever-increasing need for food, providing food security is considered one of the essential requirements in every region. On the other hand, the recent droughts are one of the main reasons for the instability in food security and food production in different regions of the world. The purpose of this research is to select a superior model in order to measure the relationship between drought parameters and food security in Alborz province. Therefore, from the data related to precipitation and temperature in order to calculate SPEI meteorological drought index, as well as the data related to the cultivated area and tonnage (tons per hectare) of the two strategic products of wheat and barley, which provide more than 43% of the province's food. It was used in a period of 21 years (1380-1400). Four methods of Spearman, ANN, ANFIS and M5 were used to investigate the relationship between drought and food security parameters in Alborz province. The results showed that in Taleghan and Karaj, the goodness of fit criteria of R2, RMSE and MAE of Spearman, ANN, ANFIS and M5 methods were from 0.752 to 0.736, 0.242 to 0.217, 0.107 to 114 respectively. 0.847 to 0.837, 0.209 to 0.253, and 0.107 to 0.111 are variable. Also, among the algorithms used, the M5 decision tree method was the best model for measuring the correlation between drought variables and food security...