The research of intelligent Decision Support system based on Case-based Reasoning in the Railway Rescue Command System

This article studies the Decision Support method that based on Case-based Reasoning (CBR), Rough Set and Expert System to construct the Railway Rescue Command System (RRCS). To do this, it takes the railway rescue case as the foundation and establishes case index and Reasoning mechanism using rough sets theory; it can effectively reduce the knowledge and discover regulation from it. For the new case, by completing the Similar Case Retrieval using Similarity Measurement theory, as well as Expert Knowledge and Rescue rules, a final Emergency Rescue Command method is obtained. The experimental results show that the decision support system which based on the above technology has obvious advantages in rescue decision-making than RBR (Ruler-based Reasoning) and experience knowledge of decision-making process.