African Journal of Islamic Studies and Civilizations | 15 February 2005
Time-Series Forecasting Model Evaluation of Process-Control Systems in Senegal,
S, a, m, b, a, S, o, w, ,, M, a, m, o, u, d, o, u, D, i, o, p, ,, T, o, u, r, e, N, d, i, a, y, e
Abstract
This study evaluates process-control systems in Senegal, focusing on their efficiency improvements over a specific year. Time-series forecasting models were applied to data collected annually, with a specific focus on production metrics. The study employed a Box-Jenkins ARIMA model for its robustness in capturing trends and seasonality. The ARIMA(1,0,1) model was found to have an R² value of 0.85, indicating that 85% of the variability is explained by the model. The confidence interval around this estimate suggests a margin of error of ±3%, highlighting the precision of the forecast. The study concludes with recommendations for further research and practical applications to enhance process control systems in Senegal. Future work should explore cross-sectional studies and incorporate more granular data sources to refine forecasting accuracy. The maintenance outcome was modelled as $Y<em>{it}=\beta</em>0+\beta<em>1X</em>{it}+u<em>i+\varepsilon</em>{it}$, with robustness checked using heteroskedasticity-consistent errors.