AN INTEGRATED AI PLATFORM COMBINING PREDICTIVE SAFETY AND FLEET OPERATIONS OPTIMIZATION (PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE KYRGYZ REPUBLIC, 2026)
This paper examines an integrated AI platform designed for flight safety management and fleet operations in the context of increasing passenger traffic and growing operational complexity in civil aviation. It is demonstrated that traditional approaches to maintenance planning and schedule management are losing effectiveness due to strong interdependencies between operational processes, rising costs, and the impact of human factors. The objective of the study is to justify the integration of predictive safety and intelligent fleet optimization within a unified platform architecture. The proposed concept is based on the application of machine learning methods to analyze operational data and predict technical risks, with subsequent integration of these assessments into operational planning processes. The results show that the implementation of an integrated AI platform reduces the likelihood of unscheduled failures, minimizes fleet downtime, and enhances the overall operational resilience of airlines.
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