A Bayesian Networks Structure Learning and Reasoning-Based Byproduct Gas Sche…

It is very crucial for the byproduct gas system in steel industry to perform an accurate and timely scheduling, which enables to reasonably utilize the energy resources and effectively reduce the production cost of enterprises. In this study, a novel datadriven-based dynamic scheduling thought is proposed for the realtime gas scheduling, in which a probability relationship described by a Bayesi…