| 书目名称 | Modeling Conflict Dynamics with Spatio-temporal Data |
| 编辑 | Andrew Zammit-Mangion,Michael Dewar,Guido Sanguine |
| 视频video | |
| 概述 | Presents a self-contained introduction to conflict modeling.Provides novel concepts which are broadly applicable.Contains supplementary material, e.g. code and data sets.Written by experts in the fiel |
| 丛书名称 | SpringerBriefs in Applied Sciences and Technology |
| 图书封面 |  |
| 描述 | 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. |
| 出版日期 | Book 2013 |
| 关键词 | Conflict Prediction; Geometric Brownian Motion; Heterogeneous Escalation; Point Process Modeling; Spatio |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-01038-0 |
| isbn_softcover | 978-3-319-01037-3 |
| isbn_ebook | 978-3-319-01038-0Series ISSN 2191-530X Series E-ISSN 2191-5318 |
| issn_series | 2191-530X |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
发表于 2025-3-21 19:50:07
