SYNTESIS OF COMPOSITE NEURAL NETWORK ARCHITECTURES FOR PREDICTIVE DATA PROCESSING IN DIGITAL INFOCOMMUNICATION EDUCATIONAL ENVIRONMENTS
This study substantiates the methodological and technical principles for synthesizing composite neural network architectures designed for predictive data processing within digital infocommunication educational environments. In the context of global digital transformation and escalating infrastructural challenges, particularly in Ukraine, the research focuses on developing adaptive systems capable of operating efficiently on resource-constrained hardware.