The research aimed to forecast the exports of United Arab Emirate (UAE) from date palm during the period (2021-2030). The R programming language was used to conduct econometric analysis in artificial intelligence, by analyzing time series of the factors influencing the UAE date palm export quantity and using the (ARIMA) methodology and construction of the artificial neural network (ANN). The results demonstrated that the influence of independent factors on the quantity of future exports was apparent, including the UAE date palm production quantity in tons (x1) at a percentage of (21.08%), domestic consumption in tons (x2) by (20.69%), mean UAE export price in dollars (x3) by (21.09%), global exports quantity in tons (x4) by (17.72%), and mean global export price in dollars (x5) by (19.42%). The (ANN) forecasted an increase in the quantity of date palm exports, reaching approximately 246 thousand tons in 2030 with a value of 232.9 million dollars. The annual growth rate of export quantity was estimated at 0.79%, with a total growth rate over the next ten years of 7.85%. Meanwhile, the annual growth rate in export value was 0.83%, with a total growth rate of 8.34%. These rates show relatively low growth, but are considered logical from an economic perspective, due to production fluctuation. The effect of independent factors on dependent variable indicated that the production quantity and export price primarily affect the export quantities, as well as rising rate of domestic consumption and global market conditions, making it inaccessible to its markets due to the intense competition.
Hasan et al. (2026) studied this question.