مجلة الدراسات المالية والمحاسبية والإدارية
Volume 9, Numéro 2, Pages 147-167
2022-12-31

Smart Forecast Of Algeria’s Unemployment Rates During 1991 – 2020



Authors : Benayad Wafaa . Halimi Wahiba .

Abstract

The current study has aimed to apply a mathematical approach of artificial intelligence, which is represented by Non-Linear Autoregressive Artificial Neural Network Model (NNAR) to forecast Algeria’s monthly unemployment rates during Dec 1991-Dec 2020, using various algorithms in the training process. By comparing the results of proposed neural networks, it has been shown that the neural network model: NAR-LM of (4-1-20-1), which based on the Back-Propagation Algorithm, has better performance than the Bayesian Regulation Neural Network model and Gradual Training Algorithm as well, where forecast error has reached a value of 3, 56*10-6. Also, the generated series by neural networks: NAR-LM (4.1.20.1) and NAR-BR (4.1.20.1) emulate well the original series compared to NAR-SCG (2.1.10.1).

Keywords

Algeria Unemployment Rate, (NNAR) Model; Back-Propagation Algorithm; Bayesian Regulation; Gradual Training Algorithm.

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