关键词: 铁路运输, 人工智能, 运行调整, 粗糙决策, 数据挖掘

Abstract: The rough set theory is a new method to deal with incomplete and uncertain data. The procedure for the theory to process data is very similar to that for the train dispatcher to make decision to adjust the conflicting trains. Both of them extract the decision-making rules from a large number of experienced data with which then the new decision are gained. Through analyzing the work of train operation adjustment and the decision-making method applied by dispatchers in detail, a model on the Rough Set is developed, and the steps for obtaining and expressing the train operation adjustment knowledge are put forward. Furthermore, the reduction algorithm of decision-making rules of train operation adjustment is also improved. All these make the conception for the method clearer and the solution making steps perfect. Finally, by mining the data of train operation from DMIS, the practicality of the algorithm method above is validated, and because the effecting extents of conditional attributes to the decision-making could be evaluated objectively from the extracted rules, the method discussed could provide valuable references for the train dispatchers to make new effective adjustment measures, and consummate train operation adjusting system on Rough Set Theory.

Key words: railway transportation, artificial intelligence, train operation adjustment, decision-making based on Rough Set, data mining