Developing hybrid ELM-ALO, ELM-LSO and ELM-SOA models for predicting advance rate of TBM

• Main Authors: Li, Chuanqi, Zhou, Jian, Tao, Ming, Du, Kun, Wang, Shaofeng, Armaghani, Danial Jahed, Mohamad, Edy Tonnizam
• Format: Article
• Published: Elsevier Ltd 2022
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/104686/; http://dx.doi.org/10.1016/j.trgeo.2022.100819

Accurate prediction of TBM performance is very important for efficient completion of TBM construction tunnel project. This paper aims to predict the advance rate (AR) of tunnel boring machine (TBM) using three hybrid models by combining three swarm intelligence optimization algorithm (Ant Lion Optim...