ANN as innovative technology for economical efficiency of educational management during crisis times

Abstract

Education today faces uncertainty and complex crises driven by economic, political, and technological challenges. Traditional management models lack the flexibility needed to ensure sustainability, making innovative solutions essential. Artificial Neural Networks (ANNs) provide powerful tools for predictive analytics, risk management, and adaptive planning in educational systems. They enable data-driven decisions, personalized learning paths, and scenario modeling under crisis conditions. Both shallow and deep ANNs improve resilience and continuity, while hybrid models combining neural and symbolic approaches enhance interpretability and adaptability. These technologies shift management from reactive strategies to proactive, predictive approaches, ensuring educational quality and stability during crises.