Abstract
Tunnel construction is a complex technology, with a huge number of effective parameters, which cannot be accurately analyzed/designed using empirical or theoretical methods. With the rapid development of computer technologies, Soft Computing (SC) approaches have been widely used in tunnel construction. Typically, the two common tunneling methods, blasting and mechanical excavation (e.g., tunnel boring machine, shield, pipe jacking method), have been used in conjunction with some SC techniques to solve specific problems and have shown a good fit. On this basis, this paper first summarizes the current research on the application of SC techniques in the field of tunnel construction methods. For example, in the case of blasting, the application of SC techniques is focusing on the environmental problems induced by blasting, such as the prediction of peak particle velocity and over-break. As for mechanical tunnel construction, the SC techniques were used to analyze the boring characteristics of the machine, such as the estimation of penetration rate and advance rate. Additionally, an important aspect for the application of SC techniques is the identification of the influencing factors for each of the study subjects, i.e. the necessary input parameters for the SC. Finally, this paper elaborates on the working process of the supervised learning models, highlights the points that need to be taken care of in each step, and points out that the SC technique, which is synergistic with the physical process, is more useful to explain the actual phenomenon.
Highlights
Tunnels, as underground space structures on transport routes, have some economic and social benefits
Tunnels built in mountainous areas can overcome topographical or elevation obstacles, improve the alignment of the route, shorten route mileage and save travel time; tunnels built in cities can reduce land use on the ground and play a positive role in guiding the traffic on the ground; tunnels built in river and strait areas do not interfere with waterway navigation, are more discreet and are less affected by the weather
Semi-controllable parameters indicate the tunnel geometry and size like the tunnel crosssection area. We considered these three groups of effective factors as input parameters for predicting Peak Particle Velocity (PPV) and over-break (Table 1)
Summary
As underground space structures on transport routes, have some economic and social benefits. The foregoing shows that tunnels play a positive role in the development of transport and accessibility to resources. At this stage, the construction scale of the tunnel is increasing, and with the rapid development of monitoring equipment and technology, researchers have access to a large amount of data during the construction process of tunnels. The construction scale of the tunnel is increasing, and with the rapid development of monitoring equipment and technology, researchers have access to a large amount of data during the construction process of tunnels Based on this data, some researchers used theoretical and empirical models to analyze some specific engineering pro-. This perspective aims to provide a general view of the application of SC techniques to solve some
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