African Electrical Engineering Journal | 08 May 2012
Time-Series Forecasting Model Evaluation for Water Treatment Facilities in Ethiopia,
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Abstract
Water treatment facilities in Ethiopia have faced challenges in maintaining consistent operational reliability due to varying water quality inputs and fluctuating demand. A time-series forecasting model was applied using ARIMA (AutoRegressive Integrated Moving Average) methodology. Robust standard errors were used to account for uncertainty in predictions. The model identified a significant positive correlation between input water quality and system efficiency, with an R² value of 0.85 indicating substantial explanatory power. The ARIMA model demonstrated high predictive accuracy, contributing to improved reliability metrics by up to 20% in Ethiopian water treatment facilities. Implementing the model could lead to more efficient resource allocation and maintenance planning for future water treatment systems. water quality forecasting, time-series analysis, ARIMA, Ethiopian water treatment 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.