Proposals for the implementation of a decision support system for air defence fire control based on fuzzy networks of targets
Proposals for the implementation of a decision support system for air defence fire control based on fuzzy networks of targets

Summary/Abstract: The purpose of the research was to improve the control of air defence firepower using fuzzynetworks of target installations, enhancing the efficiency and accuracy of defensive actions. The researchniche of this article is the optimization of decision support systems in air defence through the applicationof fuzzy logic to improve real-time threat assessment and response accuracy. The study hypothesized thatthe integration of fuzzy networks into air defence fire control would lead to improved decision-makingaccuracy and reduced response time under conditions of uncertainty. The methodology involved datacollection using radar, acoustic, and infrared sensors; modelling of fuzzy systems with specialized software;the development of fuzzy rules for threat assessment; and the simulation of real combat conditions toevaluate system effectiveness and its integration with existing detection and tracking equipment. Theresults demonstrated that the proposed decision support system significantly enhances threat assessmentaccuracy, reduces reaction time, and improves overall air defence effectiveness. Simulation tests confir-med a notable increase in the speed and precision of defensive measures, highlighting the adaptability ofthe system to dynamic combat conditions. Furthermore, the integration of fuzzy networks with existingdetection and tracking technologies facilitated rapid data processing and optimized firepower management,leading to cost reductions. The study contributes to the advancement of decision support methodologiesin air defence by introducing an innovative approach based on fuzzy logic, which enhances the accuracyand efficiency of decision-making under conditions of operational uncertainty. Future research shouldfocus on validating the system’s effectiveness in real-world deployments to further refine its performance.

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