Modeling Conflict Dynamics with Spatio-temporal Data

Nonfiction, Science & Nature, Science, Other Sciences, System Theory, Mathematics, Applied, Social & Cultural Studies, Social Science
Cover of the book Modeling Conflict Dynamics with Spatio-temporal Data by Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Guido Sanguinetti, Anaïd Flesken, Springer International Publishing
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Author: Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Guido Sanguinetti, Anaïd Flesken ISBN: 9783319010380
Publisher: Springer International Publishing Publication: September 30, 2013
Imprint: Springer Language: English
Author: Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Guido Sanguinetti, Anaïd Flesken
ISBN: 9783319010380
Publisher: Springer International Publishing
Publication: September 30, 2013
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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