| Knowledge4COVID-19

Property	Value
is ?:annotates of	<https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0008115> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0021515> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0024683> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0026338> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0026346> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0026348> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0032310> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0037186> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0041434> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0086418> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0206750> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C0700125> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C1615608> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C3694279> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C5203670> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C5203676> <https://research.tib.eu/covid-19/entity/32853285_HAS_TOPIC_C5392141>
?:authorAffiliation	[\'Taikang Pension & Insurance Co., Ltd., Beijing, China.\']
?:citedBy	-1
?:creator	<https://research.tib.eu/covid-19/entity/Bi_Xiaohui> <https://research.tib.eu/covid-19/entity/Fan_Yifan> <https://research.tib.eu/covid-19/entity/Li_Yue> <https://research.tib.eu/covid-19/entity/Li_Zhuoqun> <https://research.tib.eu/covid-19/entity/Liu_Dagong> <https://research.tib.eu/covid-19/entity/Liu_Fenglin> <https://research.tib.eu/covid-19/entity/Liu_Jiawen> <https://research.tib.eu/covid-19/entity/Mo_Steven> <https://research.tib.eu/covid-19/entity/Tong_Junliang> <https://research.tib.eu/covid-19/entity/Wang_Jie> <https://research.tib.eu/covid-19/entity/Yu_Dan> <https://research.tib.eu/covid-19/entity/Zhang_Xueting>
?:doi	<https://research.tib.eu/covid-19/entity/10.1371/journal.pone.0238280>
?:doi	10.1371/journal.pone.0238280
?:hasPublicationType	<https://research.tib.eu/covid-19/entity/Comparative_Study> <https://research.tib.eu/covid-19/entity/Journal_Article>
?:journal	PloS one
is ?:pmid of	<https://research.tib.eu/covid-19/entity/32853285>
?:pmid	<https://research.tib.eu/covid-19/entity/32853285>
?:pmid	32853285
?:publication_isRelatedTo_Disease	<https://research.tib.eu/covid-19/entity/Covid-19>
?:rankingScore_SJR	1.164
?:rankingScore_hIndex	241
?:title	Predicting and analyzing the COVID-19 epidemic in China: Based on SEIRD, LSTM and GWR models.
?:type	<https://research.tib.eu/covid-19/vocab/Publication> <https://research.tib.eu/covid-19/vocab/Publication_Author>
?:year	2020

Metadata

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