The shield machine (SM) is a complex mechanical device used for tunneling. However, the monitoring and deciding were mainly done by artificial experience during traditional construction, which brought some limitations, such as hidden mechanical failures, human operator error, and sensor anomalies. To deal with these challenges, many scholars have studied SM intelligent methods. Most of these methods only take SM into account but do not consider the SM operating environment. So, this paper discussed the relationship among SM, geological information, and control terminals. Then, according to the relationship, models were established for the control terminal, including SM rate prediction and SM anomaly detection. The experimental results show that compared with baseline models, the proposed models in this paper perform better. In the proposed model, the R2 and MSE of rate prediction can reach 92.2\%, and 0.0064 respectively. The abnormal detection rate of anomaly detection is up to 98.2\%.

Several machine learning methods can be used to predict ground conditions ahead of TBMs with high accuracy. Ensemble methods have better ground condition prediction accuracy than other machine learning models evaluated. The classification system used in characterizing the ground condition affects the performance of the machine models. The prediction performance of the machine models is different in soils and rocks of different lithologies. There have been significant advances in the use of both unsupervised and supervised machine learning (ML) methods to predict the ground condition or rock mass class ahead of tunnel boring machines (TBMs).

An image released by Tesla Motors, is a conceptual design rendering of the Hyperloop passenger transport capsule. If it were anyone else, the notion of digging hundreds of miles of tunnels to create a new subterranean transportation network under congested cities would seem like pure science fiction. But the dreamer behind this vision is Elon Musk, the billionaire innovator who has already shown with his Tesla electric cars and SpaceX rockets that he thinks big and doesn't wait for others to transform fantasy into reality. Once again, Musk is aiming to shake up an arcane industry not used to outside-the-box thinking and yet potentially ripe for disruption: the underground world of tunneling. He could use tunneling to achieve his moonshot goal of clearing up Los Angeles traffic.

Elon Musk has been teasing his tunneling project since he first tweeted the idea during a frustrated rant aimed at LA's heavy traffic in December. Now, the first details of the radical project have been revealed. In an appearance at the TED conference in Vancouver, Musk showed off a new video of electric'skates' transporting cars in a narrow tunnel under a city before raising them back to street level in a space as small as two parking spaces. At the TED conference in Vancouver, Musk showed off a new video of electric'skates' transporting cars in a narrow tunnel under a city before raising them back to street level in a space as small as two parking spaces. Behind him a Tesla car can be seen on one of the'skates.

He wants to put a human colony on Mars, fill the world with electric-powered driverless cars, charge your house with a battery and conceptualise super speed trains. Now it seems he wants to solve the scourge of traffic congestion that plagues major cities around the world. The CEO of SpaceX and Tesla has got many world-changing projects currently in the works but judging by an impromptu Twitter rant over the weekend, the innovative 45-year-old now wants to eradicate traffic congestion. On Sunday, Mr Musk was clearly frustrated by the slow moving traffic and decided to make a very public pledge to do something about it. Traffic is driving me nuts.