Command and Control System Optimalisation: Using Neural Networks to increase the Efficiency of Command Location Deployment
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F25%3A00563202" target="_blank" >RIV/60162694:G43__/25:00563202 - isvavai.cz</a>
Result on the web
<a href="https://lib.unob.cz/KONFERENCE/DK/DK_Sbornik_2024.pdf" target="_blank" >https://lib.unob.cz/KONFERENCE/DK/DK_Sbornik_2024.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Command and Control System Optimalisation: Using Neural Networks to increase the Efficiency of Command Location Deployment
Original language description
The article deals with the integration of artificial intelligence, specifically neural networks, in optimizing the deployment of command and control (C2) systems in military operations at the tactical level. Central to our research is the improvement of decision-making processes related to the strategic placement of C2 sites, considering a complex array of variables including terrain analysis, deployment of military vehicles and equipment, or adherence to military procedures. Leveraging the capabilities of neural networks, the paper proposes a novel approach to efficiently process these multifaceted data inputs to significantly improve the effectiveness and efficiency of C2 system placement. The methodology involves the development of an AI-driven framework that dynamically adapts to the evolving battlefield environment to ensure optimal command post placement that enhances operational readiness and strategic advantage. This article not only contributes to the ongoing discussion on the application of artificial intelligence in the military context, but also provides practical insights and solutions relevant to the modernization efforts of the armed forces.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
New Approaches to State Security Assurance
ISBN
978-80-7582-512-4
ISSN
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e-ISSN
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Number of pages
189
Pages from-to
10
Publisher name
University of Defence
Place of publication
Brno 2024, Czech republic
Event location
University of Defence, Brno, Czech republic
Event date
Jan 1, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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