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S-GCN-GRU-NN: A novel hybrid model by combining a Spatiotemporal Graph Convolutional Network and a Gated Recurrent Units Neural Network for short-term traffic speed forecasting
Research article (Journal of Data Information and Management, 2021) · cited 28× · AI/ML
S-GCN-GRU-NN: A novel hybrid model by combining a Spatiotemporal Graph Convolutional Network and a Gated Recurrent Units Neural Network for short-term traffic speed forecasting
Summary
S-GCN-GRU-NN: A novel hybrid model by combining a Spatiotemporal Graph Convolutional Network and a Gated Recurrent Units Neural Network for short-term traffic speed forecasting is a scholarly article[1].
Key Facts
S-GCN-GRU-NN: A novel hybrid model by combining a Spatiotemporal Graph Convolutional Network and a Gated Recurrent Units Neural Network for short-term traffic speed 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). S-GCN-GRU-NN: A novel hybrid model by combining a Spatiotemporal Graph Convolutional Network and a Gated Recurrent Units Neural Network for short-term traffic speed forecasting. Retrieved May 24, 2026, from https://4ort.xyz/entity/s-gcn-gru-nn-a-novel-hybrid-model-by-combining-a-spatiotemporal-graph-convolutional-network-and-a-gated-recurrent-units-
MLA“S-GCN-GRU-NN: A novel hybrid model by combining a Spatiotemporal Graph Convolutional Network and a Gated Recurrent Units Neural Network for short-term traffic speed forecasting.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/s-gcn-gru-nn-a-novel-hybrid-model-by-combining-a-spatiotemporal-graph-convolutional-network-and-a-gated-recurrent-units-.
BibTeX@misc{4ortxyz_s-gcn-gru-nn-a-novel-hybrid-model-by-combining-a-spatiotemporal-graph-convolutional-network-and-a-gated-recurrent-units-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{S-GCN-GRU-NN: A novel hybrid model by combining a Spatiotemporal Graph Convolutional Network and a Gated Recurrent Units Neural Network for short-term traffic speed forecasting}}, year = {2026}, url = {https://4ort.xyz/entity/s-gcn-gru-nn-a-novel-hybrid-model-by-combining-a-spatiotemporal-graph-convolutional-network-and-a-gated-recurrent-units-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): S-GCN-GRU-NN: A novel hybrid model by combining a Spatiotemporal Graph Convolutional Network and a Gated Recurrent Units Neural Network for short-term traffic speed forecasting — https://4ort.xyz/entity/s-gcn-gru-nn-a-novel-hybrid-model-by-combining-a-spatiotemporal-graph-convolutional-network-and-a-gated-recurrent-units- (retrieved 2026-05-24)
