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Publication Year: 2026

1 to 10 of 145 Results

Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction" Jan 26, 2026 Gounoue, Steve, 2026, "Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction"", https://doi.org/10.60507/FK2/DRYP80, bonndata, V2 In this repository, you can find the code to train and evaluate SCANNER+, a novel neighborhood-based self-enrichment approach for traffic speed prediction. SCANNER+ learns effective node representations in dynamic road traffic settings. This work extends SCANNER, which utilizes correlation-based pattern detection and a self-enrichment mechanism.
.gitignore Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction" Plain Text - 3.4 KB - MD5: be85f81e6cc8066629a0464226450c3c
config.py Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction" Python Source Code - 4.9 KB - MD5: 0389a89900e28058294d79ee957393cf
correlations.py Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction" Python Source Code - 4.1 KB - MD5: 3dafcd83c5833accf319e6363b0521c4
LICENSE Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction" Plain Text - 1.0 KB - MD5: 9166a54d6b45565ba0e1420c2de7fdf0
loader.py Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction" Python Source Code - 9.6 KB - MD5: 0bc47c5210de4b0479c71c968b9aadb9
main.py Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction" Python Source Code - 2.8 KB - MD5: 1d18549aaaf4c8b13ae9e2a6855f1099
metrics.py Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction" Python Source Code - 3.6 KB - MD5: 821a8b8c9d075a387d5c5901b31c4b84
models.py Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction" Python Source Code - 11.7 KB - MD5: c9ea92936a88e78c8e37215c261226da
README.md Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction" Markdown Text - 4.1 KB - MD5: e0d58f8633a84bea05fec828fc1e5f07

Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction"

Jan 26, 2026

Gounoue, Steve, 2026, "Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction"", https://doi.org/10.60507/FK2/DRYP80, bonndata, V2

In this repository, you can find the code to train and evaluate SCANNER+, a novel neighborhood-based self-enrichment approach for traffic speed prediction. SCANNER+ learns effective node representations in dynamic road traffic settings. This work extends SCANNER, which utilizes correlation-based pattern detection and a self-enrichment mechanism.

.gitignore

Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction"

Plain Text - 3.4 KB -

config.py

Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction"

Python Source Code - 4.9 KB -

correlations.py

Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction"

Python Source Code - 4.1 KB -

LICENSE

Jan 26, 2026 - Implementation of the paper "SCANNER+: Neighborhood-based self-enrichment approach for traffic speed prediction"

Plain Text - 1.0 KB -