Methodological Evaluation of Field Research Stations Systems in Ethiopia Using Time-Series Forecasting Models

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Main Authors: Asfaweghiya, Mekonnen, Woldebrhan, Yared
Format: Recurso digital
Language:English
Published: Zenodo 2003
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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