Using artificial networks to predict Algerian oil prices (Saharan Blend)

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Hadj Kouider Abdelhadi, Benlaria Ahmed, Baghafar Abdelkader


    This study explores the efficacy of Artificial Neural Networks (ANN) in forecasting monthly crude oil prices. Utilizing data from January 1990 to August 2023, an ANN model was developed and trained to predict future values. The results were promising, showing a strong correlation with actual prices and underscoring the potential of ANNs in financial forecasting. The research indicates that machine learning can significantly contribute to the predictive analytics in the energy market, offering a valuable tool for economic and strategic planning.

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