SPATIO-TEMPORAL CRIME PREDICTION
| dc.contributor.advisor | Ella Haig | |
| dc.contributor.author | MOHAMMED AMER HAMED ALANEZI | |
| dc.date | 2019 | |
| dc.date.accessioned | 2022-05-26T16:52:06Z | |
| dc.date.available | 2022-05-26T16:52:06Z | |
| dc.degree.department | Data Analytics | |
| dc.degree.grantor | University of Portsmouth- School of Computing | |
| dc.description.abstract | this study proposed a spatio-temporal model to detect the regions having high crime density (called hotspots) and then predict the crime based with the temporal features. It was intended to divide the total area into smaller regions based on the crime density, identify the denser regions and then predict the crime patterns for the future based upon the previous trends. That can help the authorities and the police to devise efficient strategies and plans for better allocation of resources. | |
| dc.identifier.uri | https://drepo.sdl.edu.sa/handle/20.500.14154/30503 | |
| dc.language.iso | en | |
| dc.title | SPATIO-TEMPORAL CRIME PREDICTION | |
| sdl.thesis.level | Master | |
| sdl.thesis.source | SACM - United Kingdom |