Study On The Application Of Rough Set-Based Knowledge Acquisition And Decision In Train Traffic Control

The train traffic control is the railway transportation high-tech centralism manifests, makes the best of the transport capacity which railroad itself has, is the important guarantees for the railroad movement security. This article for the first time unifies the rough set theory and the train traffic control, induces and sum up the policy-making attribute in the train traffic control process, has established the integrity intelligence decision system by the train traffic control knowledge acquisition, self-study and the assistance decision-making support to the dispatcher based on the rough set theory, has provided the new method for the train traffic control intellectualization.This article has carried on the analysis to the existing train traffic control application process, discovers the questions existed, then embarked from the rough set theory, has established the intelligence decision-making process model based on the rough set theory; through the train traffic control rough set knowledge expression analysis, it discovered that there are two objective adjustment procedures during the train in the actual movement process, namely the nature adjustment procedure and the manual involvement adjustment procedure. The nature adjustment procedure is in the train movement process, the dispatcher does not intervene the train's movement, but only supervise the train's movement; only has the conflicts between the two trains' movements, the dispatcher then carries on the adjustment to the train movement. These two processes proposed is advantageous to the discovery of adjustment essence, enhances the adjustment's actual effect and validity.Through to the train traffic control rough set decision-making appraisal analysis, this article has established the adult department's analysis theory to it.Finally, proposed the integrity train traffic control decision system, fully elaborated train traffic control process and the method based on the rough set theory.