Citation

Brown D, Dalton J, Hoyle H. Lect. Notes Comput. Sci. 2004; 3073: 426-435.

Copyright

(Copyright © 2004, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/978-3-540-25952-7_33

PMID

unavailable

Abstract

Terrorist events such as suicide bombings are rare yet extremely destructive events. Responses to such events are even rarer, because they require forecasting methods for effective prevention and early detection. While many forecasting methods are available, few are designed for conflict scenarios. This paper builds on previous work in forecasting criminal behavior using spatial choice models. Specifically we describe the fusion of two techniques for modeling the spatial choice of suicide bombers into a unified forecast that combines spatial likelihood modeling of environmental characteristics with logistic regression modeling of demographic features. In addition to describing the approach we also provide motivation for the fusion of the methods and contrast the results obtained with those from the more common kernel density estimation methods that do not account for variation in the event space. We give an example of successful use of this combined method and an evaluation of its performance. We conclude that the fusion method shows improvement over other methods and greater scalability for combining larger numbers of spatial forecasting methods than were previously available. © Springer-Verlag Berlin Heidelberg 2004.

Language: en

Keywords

Terrorism; Forecasting; Demographic features; Environmental characteristic; Forecasting methods; Kernel Density Estimation methods; Logistic Regression modeling; Spatial forecasts; Terrorist events; Urban environments