The objective of this work is to take advantage of deep neural networks in order to make next day crime count predictions in a fine-grain city partition. We make predictions using Chicago and Portland crime data, which is augmented with additional datasets covering weather, census data, and public transportation. The crime counts are broken into 10 bins and our model predicts the most likely bin for a each spatial region at a daily level. We train this data using increasingly complex neural network structures, including variations that are suited to the spatial and temporal aspects of the crime prediction problem. With our best model we are able to predict the correct bin for overall crime count with 75.6 and 65.3 accuracy for Chicago and Portland, respectively. The results show the efficacy of neural networks for the prediction problem and the value of using external datasets in addition to standard crime data.
Methods used for crime prediction have changed greatly over the years as new analytics-based software was introduced. Geographical Information Systems (GIS) were the first and are the most widespread analytic tool for spatial data @cite_0 . GIS is quite useful at producing maps and retrospectively finding links between crime patterns and various spatial and social conditions @cite_11 @cite_8 , but does not provide much predictive power on its own.
@cite_0 @cite_8 @cite_11
612782763 2512173100
An introduction to three of the growing number of sophisticated extensions that add power to the core GIS software. The Third Edition of this bestselling textbook has been fully revised and updated to include the latest developments in the field and still retains its accessible format to appeal to a broad range of students.Now divided into five clear sections the book investigates the unique, complex and difficult problems that are posed by geographic information and together they build into a holistic understanding of the key principles of GIS.This is the most current, authoritative and comprehensive treatment of the field, that goes from fundamental principles to the big picture of:GIS and the New World Ordersecurity, health and well-beingdigital differentiation in GIS consumptionthe core organizing role of GIS in Geographythe greening of GISgrand challenges of GISciencescience and explanationKey features:Four-colour throughoutAssociated website with free online resourcesTeachers manual available for lecturersA complete learning resource, with accompanying instructor links, free online lab resources and personal syllabiIncludes learning objectives and review boxes throughout each chapterNew in this edition:Completely revised with a new five part structure: Foundations; Principles; Techniques; Analysis; Management and PolicyAll new personality boxes of current GIS practitionersNew chapters on Distributed GIS, Map Production, Geovisualization, Modeling, and Managing GIS