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Stochastic (S[ARIMA]), shallow (NARnet, NAR-GMDH, OS-ELM), and deep learning (LSTM, Stacked-LSTM, CNN-GRU) models, application to river flow forecasting
Research article (Acta Geophysica, 2023) · cited 19× · AI/ML
Stochastic (S[ARIMA]), shallow (NARnet, NAR-GMDH, OS-ELM), and deep learning (LSTM, Stacked-LSTM, CNN-GRU) models, application to river flow forecasting
Summary
Stochastic (S[ARIMA]), shallow (NARnet, NAR-GMDH, OS-ELM), and deep learning (LSTM, Stacked-LSTM, CNN-GRU) models, application to river flow forecasting is a scholarly article[1].
Key Facts
Stochastic (S[ARIMA]), shallow (NARnet, NAR-GMDH, OS-ELM), and deep learning (LSTM, Stacked-LSTM, CNN-GRU) models, application to river flow forecasting'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). Stochastic (S[ARIMA]), shallow (NARnet, NAR-GMDH, OS-ELM), and deep learning (LSTM, Stacked-LSTM, CNN-GRU) models, application to river flow forecasting. Retrieved May 24, 2026, from https://4ort.xyz/entity/stochastic-s-arima-shallow-narnet-nar-gmdh-os-elm-and-deep-learning-lstm-stacked-lstm-cnn-gru-models-application-to-rive
MLA“Stochastic (S[ARIMA]), shallow (NARnet, NAR-GMDH, OS-ELM), and deep learning (LSTM, Stacked-LSTM, CNN-GRU) models, application to river flow forecasting.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/stochastic-s-arima-shallow-narnet-nar-gmdh-os-elm-and-deep-learning-lstm-stacked-lstm-cnn-gru-models-application-to-rive.
BibTeX@misc{4ortxyz_stochastic-s-arima-shallow-narnet-nar-gmdh-os-elm-and-deep-learning-lstm-stacked-lstm-cnn-gru-models-application-to-rive_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Stochastic (S[ARIMA]), shallow (NARnet, NAR-GMDH, OS-ELM), and deep learning (LSTM, Stacked-LSTM, CNN-GRU) models, application to river flow forecasting}}, year = {2026}, url = {https://4ort.xyz/entity/stochastic-s-arima-shallow-narnet-nar-gmdh-os-elm-and-deep-learning-lstm-stacked-lstm-cnn-gru-models-application-to-rive}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Stochastic (S[ARIMA]), shallow (NARnet, NAR-GMDH, OS-ELM), and deep learning (LSTM, Stacked-LSTM, CNN-GRU) models, application to river flow forecasting — https://4ort.xyz/entity/stochastic-s-arima-shallow-narnet-nar-gmdh-os-elm-and-deep-learning-lstm-stacked-lstm-cnn-gru-models-application-to-rive (retrieved 2026-05-24)
