Publication Date: 2024/01/16
Abstract: Several Artificial intelligence techniques can help predict future values of time and provide guidance on social and economic development plans. The goal of this study was to analyze the Iraqi economy using neural networks. It was able to predict the country's gross domestic product from 2003 to 2020. Thirty-six networks of different types (feed-forward backpropagation, NARX, Layer Recurrent Network (LRN)) were built. The recommended model was chosen according to the RMSE criterion. The Iraqi GDP prediction was made using an artificial neural network that utilized the TRAINBR training and transit functions. It performed well and earned the lowest error value.
Keywords: Gross Domestic Product, Time Series, Artificial Neural Networks.
DOI: https://doi.org/10.5281/zenodo.10516679
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24JAN251.pdf
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