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Advances in land surface forecasting: a comparison of LSTM, gradient boosting, and feed-forward neural networks as prognostic state emulators in a case study with ecLand
Research article (Geoscientific model development, 2025) · cited 10× · AI/ML
Advances in land surface forecasting: a comparison of LSTM, gradient boosting, and feed-forward neural networks as prognostic state emulators in a case study with ecLand
Summary
Advances in land surface forecasting: a comparison of LSTM, gradient boosting, and feed-forward neural networks as prognostic state emulators in a case study with ecLand is a scholarly article[1].
Key Facts
Advances in land surface forecasting: a comparison of LSTM, gradient boosting, and feed-forward neural networks as prognostic state emulators in a case study with ecLand'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). Advances in land surface forecasting: a comparison of LSTM, gradient boosting, and feed-forward neural networks as prognostic state emulators in a case study with ecLand. Retrieved May 24, 2026, from https://4ort.xyz/entity/advances-in-land-surface-forecasting-a-comparison-of-lstm-gradient-boosting-and-feed-forward-neural-networks-as-prognost
MLA“Advances in land surface forecasting: a comparison of LSTM, gradient boosting, and feed-forward neural networks as prognostic state emulators in a case study with ecLand.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/advances-in-land-surface-forecasting-a-comparison-of-lstm-gradient-boosting-and-feed-forward-neural-networks-as-prognost.
BibTeX@misc{4ortxyz_advances-in-land-surface-forecasting-a-comparison-of-lstm-gradient-boosting-and-feed-forward-neural-networks-as-prognost_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Advances in land surface forecasting: a comparison of LSTM, gradient boosting, and feed-forward neural networks as prognostic state emulators in a case study with ecLand}}, year = {2026}, url = {https://4ort.xyz/entity/advances-in-land-surface-forecasting-a-comparison-of-lstm-gradient-boosting-and-feed-forward-neural-networks-as-prognost}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Advances in land surface forecasting: a comparison of LSTM, gradient boosting, and feed-forward neural networks as prognostic state emulators in a case study with ecLand — https://4ort.xyz/entity/advances-in-land-surface-forecasting-a-comparison-of-lstm-gradient-boosting-and-feed-forward-neural-networks-as-prognost (retrieved 2026-05-24)
