Research on Equipment Support Command Issues Based on Intelligent Decision-making


Baosheng Zhang*, Hui Wang, Shoulun Wang, Jing Lu

Army Academy of Armored Forces, Beijing, China.

*Corresponding author: Baosheng Zhang

Published: January 18,2024


This comprehensive study delves into the integration of artificial intelligence (AI) in military vehicle equipment support, highlighting the potential and challenges of AI in this critical area. It emphasizes the need for intelligent decision-making systems that are robust and adaptable to the unpredictable nature of combat environments. The paper discusses the technical aspects of integrating AI into existing systems, ensuring compatibility and seamless operation. A significant focus is on the development of advanced AI models that leverage mathematical algorithms to improve decision-making accuracy and efficiency. Operational challenges are also addressed, with an emphasis on using AI to enhance command and control capabilities. The study suggests incorporating real-time data analytics into military operations to provide commanders with up-to-date information, facilitating more informed and timely decisions. This approach aims to improve the overall effectiveness of military logistics and operations. The ethical dimension of AI integration in military contexts is a key concern. The paper advocates for the development and updating of policies that govern the ethical and secure use of AI in military operations. These policies must address issues like data privacy, AI autonomy, and the potential consequences of AI-driven decisions in combat scenarios. Overall, the study proposes a multi-dimensional approach to AI integration in military vehicle equipment support. By addressing technical, operational, and ethical challenges, it aims to optimize the use of AI in military logistics and ensure its effective application in complex and dynamic operational environments. The goal is to enhance military capabilities while maintaining ethical standards and operational security.


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How to cite this paper

Research on Equipment Support Command Issues Based on Intelligent Decision-making

How to cite this paper: Baosheng Zhang, Hui Wang, Shoulun Wang, Jing Lu. (2023) Research on Equipment Support Command Issues Based on Intelligent Decision-making. Advances in Computer and Communication4(6), 400-405.