USING THE CHAOTIC GENETIC ALGORITHM METHOD TO PREDICT OIL WITH AN APPLICATION

Abstract

Interest in the area of prediction has risen in recent years, leading to the development of advanced and contemporary methods, namely artificial intelligence techniques. Among these methods is the chaotic genetic algorithm, which has proven its quality in this regard, as the chaotic genetic algorithm expands the search space due to its strength and effectiveness in solving many complex nonlinear optimization problems. Our current study aims to shed light on the chaotic genetic algorithm method in predicting future oil production and prices in Iraq. The results showed that the chaotic genetic algorithm (CGA) method performs much better than the genetic algorithm (GA) method in terms of accuracy, reducing the number of iterations in optimization problems, and avoiding local convergence to reach the optimal level in predicting Iraqi oil until the year 2035.