Study and design of Shield-driven Tunnel Risk Control knowledge management system based on combined reasoning technique

Abstract

As using a single reasoning technique is more and more difficult to meet the demand of the complicated systems, the study of a combined reasoning mechanism with two or more reasoning techniques integrated is becoming an important trend of artificial intelligence area to design knowledge system. In this paper, knowledge management theory is introduced to Shield-driven Tunnel Risk Control management field and takes on a new perspective to explore the shield-driven tunnel project risk management techniques and methods. A combined reasoning machine model, which is based on the extended rule reasoning and case reasoning, is proposed to design and explore the risk control of tunnel construction, and based on this model, a software—Tunneling Risk Control Knowledge Management System (TRCKMS) is designed to assist technicians to manage tunneling risk more efficiently and safely.