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ica-proc-1-12-2018.pdf
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🔗 Source: ica-proc.copernicus.org
📊 Size: 3.14 MB
👤 Author: Windows-felhasználó
⬇️ Downloads: 62

Summary

Researchers analyzed city-wide parking meter data from Hannover, Germany, to identify typical parking occupancy patterns. They applied data cleansing and hierarchical clustering to group parking meters with similar daily patterns, determining the optimal number of clusters using the Davies-Bouldin Index and Silhouette Index. The results showed three clusters with distinct temporal patterns, mainly differing in the hour of maximum occupancy, and clear spatial distinctions between clusters. The study aims to assist drivers in avoiding crowded roads and inform policymakers about parking price adaptations.

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Description

Researchers analyzed city-wide parking meter data from Hannover, Germany, to identify typical parking occupancy patterns.

Technical Information

  • File Format: PDF
  • File Size: 3.14 MB
  • Pages: 5
  • Language: EN
  • Author: Windows-felhasználó
  • Total Downloads: 62
  • Last Updated: 3 hours ago

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