Event-driven architecture and intelligent decision tree facilitated sustainable trade activity monitoring model design.

ABSTRACT: This paper introduces a groundbreaking monitoring model tailored for sustainable trade activity surveillance, which synergistically integrates event-driven architecture with an intelligent decision tree. Confronting the constraints of conventional trade monitoring approaches that falter in adapting to the intricate and ever-changing market landscape, our model innovatively establishes an efficient, adaptable, and sustainable monitoring framework. By embedding an intelligent decision tree, it enables dynamic resource allocation, thereby optimizing operational efficacy. Initially, we devise rules that align data injection and processing velocities, ensuring expedient data processing. Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming,

SUBMITTER: Wen Y 

PROVIDER: S-EPMC12410814 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature