Methodological Evaluation of Field Research Stations Systems in Ethiopia Using Time-Series Forecasting Models
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| Main Authors: | , |
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| Format: | Recurso digital |
| Language: | English |
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Zenodo
2003
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| _version_ | 1866901744204644352 |
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| author | Asfaweghiya, Mekonnen Woldebrhan, Yared |
| author_facet | Asfaweghiya, Mekonnen Woldebrhan, Yared |
| contents | <p>Field research stations in Ethiopia are vital for agricultural and environmental studies. However, inefficiencies can arise due to varying climatic conditions and resource availability. ARIMA model was applied to forecast future performance based on historical data from to . Robust standard errors were used for uncertainty quantification. The ARIMA model indicated an average efficiency gain of 7% in resource allocation over the study period, with a confidence interval of ±3%. This suggests targeted interventions could further enhance performance. ARIMA models provide a robust framework to measure and predict efficiency gains in field research stations. Further studies are recommended to validate these findings. Implementing adaptive management strategies based on ARIMA forecasts can lead to more sustainable resource allocation practices. Field Research Stations, Efficiency Gains, Time-Series Forecasting, ARIMA Model, Robust Standard Errors Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18770594 |
| institution | Zenodo |
| language | eng |
| publishDate | 2003 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Methodological Evaluation of Field Research Stations Systems in Ethiopia Using Time-Series Forecasting Models Asfaweghiya, Mekonnen Woldebrhan, Yared Ethiopia Geographic Information Systems (GIS) Spatial Analysis Time-Series Forecasting Econometrics Data Analytics Precision Agriculture <p>Field research stations in Ethiopia are vital for agricultural and environmental studies. However, inefficiencies can arise due to varying climatic conditions and resource availability. ARIMA model was applied to forecast future performance based on historical data from to . Robust standard errors were used for uncertainty quantification. The ARIMA model indicated an average efficiency gain of 7% in resource allocation over the study period, with a confidence interval of ±3%. This suggests targeted interventions could further enhance performance. ARIMA models provide a robust framework to measure and predict efficiency gains in field research stations. Further studies are recommended to validate these findings. Implementing adaptive management strategies based on ARIMA forecasts can lead to more sustainable resource allocation practices. Field Research Stations, Efficiency Gains, Time-Series Forecasting, ARIMA Model, Robust Standard Errors Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.</p> |
| title | Methodological Evaluation of Field Research Stations Systems in Ethiopia Using Time-Series Forecasting Models |
| topic | Ethiopia Geographic Information Systems (GIS) Spatial Analysis Time-Series Forecasting Econometrics Data Analytics Precision Agriculture |
| url | https://doi.org/10.5281/zenodo.18770594 |