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AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models
Research article (Agronomy, 2022) · cited 19× · AI/ML
AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models
Summary
AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models is a scholarly article[1].
Key Facts
AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models. Retrieved May 24, 2026, from https://4ort.xyz/entity/agroml-an-open-source-repository-to-forecast-reference-evapotranspiration-in-different-geo-climatic-conditions-using-mac
MLA“AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/agroml-an-open-source-repository-to-forecast-reference-evapotranspiration-in-different-geo-climatic-conditions-using-mac.
BibTeX@misc{4ortxyz_agroml-an-open-source-repository-to-forecast-reference-evapotranspiration-in-different-geo-climatic-conditions-using-mac_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models}}, year = {2026}, url = {https://4ort.xyz/entity/agroml-an-open-source-repository-to-forecast-reference-evapotranspiration-in-different-geo-climatic-conditions-using-mac}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): AgroML: An Open-Source Repository to Forecast Reference Evapotranspiration in Different Geo-Climatic Conditions Using Machine Learning and Transformer-Based Models — https://4ort.xyz/entity/agroml-an-open-source-repository-to-forecast-reference-evapotranspiration-in-different-geo-climatic-conditions-using-mac (retrieved 2026-05-24)
