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Strategic Forecasting with Machine Learning for Geopolitical Analysis

  • Strategic forecasting of regional geopolitical development is important for early warning and contingency planning. Open source data and machine learning can help to identify indicators for effective scenario development. Using data of the Bertelsmann Transformation Index (BTI) and the machine learning software Waikato Environment for Knowledge Analysis (WEKA), this paper gives an insight into the generation of a decision tree to provide indicators for forecasting regional development across parts of Northern and Western Africa. Results show that machine learning with open source data can support redefining indicator development but does not replace critical thinking.

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Metadaten
Author:Markus BresinskyGND, J. Schröder, Valerio Viscardi
URL / DOI:https://drive.google.com/file/d/1o2qAxcnq5srRr8r8okibHWwb4O0c69Oz/view
ISBN:978-618-00-2351-0
Parent Title (Multiple languages):Η Περιφερειακή Επιστήμη, το μέλλον της και οι προκλήσεις στα πεδία της έρευνας και της εφαρμογής : 21ο Επιστημονικό Συνέδριο του Συνδέσμου Ελλήνων Περιφερειολόγων Ελληνικό Μεσογειακό Πανεπιστήμιο, Ηράκλειο Κρήτης, 16-17 Οκτωβρίου 2020 - Challenges for the Future of Regional Science: Research and Applications; 21st Conference: Heraklion, Crete, Oktober 2020
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2020
Release Date:2022/01/28
First Page:267
Last Page:276
Institutes:Fakultät Angewandte Natur- und Kulturwissenschaften
research focus:Sensorik
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG