This Data Descriptor focuses on the analysis of municipal infrastructure assets systems in Ethiopia, aiming to evaluate system reliability through a time-series forecasting model. A time-series forecasting model was employed, incorporating ARIMA (AutoRegressive Integrated Moving Average) for the analysis. Uncertainty around forecasts is quantified with 95% confidence intervals. The forecasting model demonstrated a strong correlation (R² = 0. 84), indicating that it effectively predicts system reliability trends over time. The direction of change in asset condition was predominantly positive, reflecting improvements over the forecast period. The findings suggest that the proposed ARIMA model can reliably predict changes in municipal infrastructure asset conditions in Ethiopia, offering a valuable tool for policy and investment planning. Further research should investigate long-term forecasting and explore potential interventions to mitigate any negative trends identified by the model. Ethiopia, municipal infrastructure, time-series forecasting, system reliability, ARIMA
Demeknawī et al. (Mon,) studied this question.
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