Associative Rules for Modeling International Security Decisions in the Context of the Ukrainian-Russian War. Preliminary Evaluations
Author:
Berezka Kateryna M.1ORCID, Kovalchuk Olha Ya.2ORCID
Affiliation:
1. 1 Department of Applied Mathematics , West Ukrainian National University , Ukraine 2. 2 Department of Applied Mathematics , West Ukrainian National University , Ukraine
Abstract
Abstract
Research background
By launching a war against Ukraine, Russia changed the entire world system and demonstrated the ineffectiveness of the global security system. Today it is necessary to look for effective solutions to support the adoption of security decisions and develop effective strategies for the formation of a new architecture of the international security system.
Purpose
The paper aims to obtain preliminary approximate estimates of the state commitments of the countries of the world that support Ukraine in the war with Russia and to reveal non-obvious connections and regularities in the provision of various types of aid.
Research methodology
The data were collected on the rough refugee cost estimate, quantitative assessment of the government-to-government commitments, and preliminary data on non-bilateral aid transferred by governments to Ukraine of 40 countries. We used the FP-Growth algorithm to identify non-obvious connections and patterns between different types of support for Ukraine.
Results
We created an associative rules model to detect non-obvious patterns and relationships between the different types of bilateral commitments of the countries, that support Ukraine.
Novelty
Preliminary estimates were obtained between various types of international support for Ukraine in the war against Russia covering February 24 to November 20, 2022, the number of Ukrainian refugees accepted by the respective countries, and the sale of arms to Russia by some of them after the ban.
Publisher
Walter de Gruyter GmbH
Subject
General Economics, Econometrics and Finance,Organizational Behavior and Human Resource Management,Marketing,Business, Management and Accounting (miscellaneous)
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