Forecasting Sales of Iraqi Dates Using Artificial Intelligence

Abstract

Iraq is considered one of the first countries in the world to export Dates of all kinds. This sector at present needs support and serious work to improve sales to provide the country's economy with more revenues. This study proposes building an integrated artificial intelligence model that predicts the quantities of Dates that Iraq will produce in the coming years based on previous data and based on two main points: The first point is to make a comparison between three different food datasets with a different correlation between their features, as the first dataset is of high correlation, the second is of medium correlation, and the third is of weak correlation. The second point is to apply twelve Machine Learning algorithms and evaluate their results to obtain the best three algorithms. The model was applied to predict the quantities of Dates that Iraq will produce for the next five years. The proposed three algorithms were used and gave the following results: (Gradient Boosting: 99.51, Random Forest: 97.05, and Bagging Regressor: 98.54). This study constitutes a starting point for future studies in terms of the process of choosing the datasets, as well as the machine learning technique.