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Statistical and deep learning models for reference evapotranspiration time series forecasting: A comparison of accuracy, complexity, and data efficiency
Research article (Computers and Electronics in Agriculture, 2023) · cited 35× · AI/ML
Statistical and deep learning models for reference evapotranspiration time series forecasting: A comparison of accuracy, complexity, and data efficiency
Summary
Statistical and deep learning models for reference evapotranspiration time series forecasting: A comparison of accuracy, complexity, and data efficiency is a scholarly article[1].
Key Facts
Statistical and deep learning models for reference evapotranspiration time series forecasting: A comparison of accuracy, complexity, and data efficiency's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Statistical and deep learning models for reference evapotranspiration time series forecasting: A comparison of accuracy, complexity, and data efficiency. Retrieved May 24, 2026, from https://4ort.xyz/entity/statistical-and-deep-learning-models-for-reference-evapotranspiration-time-series-forecasting-a-comparison-of-accuracy-c
MLA“Statistical and deep learning models for reference evapotranspiration time series forecasting: A comparison of accuracy, complexity, and data efficiency.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/statistical-and-deep-learning-models-for-reference-evapotranspiration-time-series-forecasting-a-comparison-of-accuracy-c.
BibTeX@misc{4ortxyz_statistical-and-deep-learning-models-for-reference-evapotranspiration-time-series-forecasting-a-comparison-of-accuracy-c_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Statistical and deep learning models for reference evapotranspiration time series forecasting: A comparison of accuracy, complexity, and data efficiency}}, year = {2026}, url = {https://4ort.xyz/entity/statistical-and-deep-learning-models-for-reference-evapotranspiration-time-series-forecasting-a-comparison-of-accuracy-c}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Statistical and deep learning models for reference evapotranspiration time series forecasting: A comparison of accuracy, complexity, and data efficiency — https://4ort.xyz/entity/statistical-and-deep-learning-models-for-reference-evapotranspiration-time-series-forecasting-a-comparison-of-accuracy-c (retrieved 2026-05-24)
