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). Predicting and analyzing the COVID-19 epidemic in China: Based on SEIRD, LSTM and GWR models. Retrieved May 24, 2026, from https://4ort.xyz/entity/predicting-and-analyzing-the-covid-19-epidemic-in-china-based-on-seird-lstm-and-gwr-models
MLA“Predicting and analyzing the COVID-19 epidemic in China: Based on SEIRD, LSTM and GWR models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/predicting-and-analyzing-the-covid-19-epidemic-in-china-based-on-seird-lstm-and-gwr-models.
BibTeX@misc{4ortxyz_predicting-and-analyzing-the-covid-19-epidemic-in-china-based-on-seird-lstm-and-gwr-models_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Predicting and analyzing the COVID-19 epidemic in China: Based on SEIRD, LSTM and GWR models}}, year = {2026}, url = {https://4ort.xyz/entity/predicting-and-analyzing-the-covid-19-epidemic-in-china-based-on-seird-lstm-and-gwr-models}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Predicting and analyzing the COVID-19 epidemic in China: Based on SEIRD, LSTM and GWR models — https://4ort.xyz/entity/predicting-and-analyzing-the-covid-19-epidemic-in-china-based-on-seird-lstm-and-gwr-models (retrieved 2026-05-24)
