Command and Control System Optimalisation: Using Neural Networks to increase the Efficiency of Command Location Deployment

Kód výsledku v 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>

Výsledek na webu

<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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Jazyk výsledku

angličtina

Název v původním jazyce

Command and Control System Optimalisation: Using Neural Networks to increase the Efficiency of Command Location Deployment

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Command and Control System Optimalisation: Using Neural Networks to increase the Efficiency of Command Location Deployment

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20205 - Automation and control systems

Projekt

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Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

New Approaches to State Security Assurance

ISBN

978-80-7582-512-4

ISSN

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e-ISSN

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Počet stran výsledku

189

Strana od-do

10

Název nakladatele

University of Defence

Místo vydání

Brno 2024, Czech republic

Místo konání akce

University of Defence, Brno, Czech republic

Datum konání akce

1. 1. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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