Deep Learning for Crime Forecasting of Multiple Regions, Considering Spatial–Temporal Correlations between Regions
Crime forecasting has gained popularity in recent years; however, the majority of studies have been conducted in the United States, which may result in a bias towards areas with a substantial population. In this study, we generated different models capable of forecasting the number of crimes in 83 r...
Saved in:
| Main Authors: | Martín Solís, Luis-Alexander Calvo-Valverde |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-06-01
|
| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/68/1/4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Spatial-Temporal Fusion Graph Neural Networks With Mixed Adjacency for Weather Forecasting
by: Ang Guo, et al.
Published: (2025-01-01) -
The Relevance of Spatial and Temporal Connections and Relationships for the Formation of a Subtheory of Forensic Forecasting
by: I. V. Ustinova
Published: (2021-04-01) -
Intra-prediction mode decision based on video temporal and spatial correlation
by: DAI Sheng-kui, et al.
Published: (2005-01-01) -
Ultra-short-term Probabilistic Forecasting of Distributed Photovoltaic Power Generation Based on Hierarchical Correlation Modeling
by: Can CHEN, et al.
Published: (2024-12-01) -
Unveiling urban violence crime in the State of the Selangor, Kuala Lumpur and Putrajaya: a spatial–temporal investigation of violence crime in Malaysia’s key cities
by: Azizul Ahmad, et al.
Published: (2024-12-01)