Predicting Safe Parking Spaces: A Machine Learning Approach to Geospatial Urban and Crime Data

Predicting Safe Parking Spaces: A Machine Learning Approach to Geospatial Urban and Crime Data

This research aims to identify spatial and time patterns of theft in Manhattan, NY, to reveal urban factors that contribute to thefts from motor vehicles and to build a prediction model for thefts. Methods include time series and hot spot analysis, linear regression, elastic-net, Support vector mach...

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Bibliographic Details
Main Authors: Irina Matijosaitiene, Anthony McDowald, Vishal Juneja
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Sustainability
Subjects:
geospatial data
machine learning
Manhattan
prediction model
theft from motor vehicle
crime prevention through urban planning
Online Access:https://www.mdpi.com/2071-1050/11/10/2848

Internet

https://www.mdpi.com/2071-1050/11/10/2848

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