Modeling Conflict Dynamics with Spatio-temporal Data - Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Anaïd Flesken, Guido Sanguinetti

Modeling Conflict Dynamics with Spatio-temporal Data

Buch | Softcover
VIII, 74 Seiten
2013 | 2013
Springer International Publishing (Verlag)
978-3-319-01037-3 (ISBN)
54,99 inkl. MwSt
This authored monograph presents the use of dynamic spatiotemporal modeling tools for the identification of complex underlying processes in conflict, such as diffusion, relocation, heterogeneous escalation, and volatility. The authors use ideas from statistics, signal processing, and ecology, and provide a predictive framework which is able to assimilate data and give confidence estimates on the predictions.
The book also demonstrates the methods on the WikiLeaks Afghan War Diary, the results showing that this approach allows deeper insights into conflict dynamics and allows a strikingly statistically accurate forward prediction of armed opposition group activity in 2010, based solely on data from preceding years. The target audience primarily comprises researchers and practitioners in the involved fields but the book may also be beneficial for graduate students.

Conflict Data Sets and Point Patterns.- Theory.- Modelling and Prediction in Conflict: Afghanistan.

Erscheint lt. Verlag 11.10.2013
Reihe/Serie SpringerBriefs in Applied Sciences and Technology
SpringerBriefs in Mathematical Methods
Zusatzinfo VIII, 74 p. 13 illus., 1 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 152 g
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
Naturwissenschaften Physik / Astronomie Theoretische Physik
Sozialwissenschaften Soziologie Empirische Sozialforschung
Schlagworte Complexity • Conflict Prediction • Data-driven Science, Modeling and Theory Building • Geometric Brownian motion • Heterogeneous Escalation • Point Process Modeling • Spatiotemporal Modeling • WikiLeaks Afghan War Diary
ISBN-10 3-319-01037-9 / 3319010379
ISBN-13 978-3-319-01037-3 / 9783319010373
Zustand Neuware
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