Proposing several hybrid PSO-extreme learning machine techniques to predict TBM performance

Zeng, J; Roy, B; Kumar, D; Mohammed, AS; Armaghani, DJ; Zhou, J; Mohamad, ET

Armaghani, DJ (corresponding author), Duy Tan Univ, Inst Res & Dev, Da Nang 550000, Vietnam.; Armaghani, DJ (corresponding author), Univ Teknol Malaysia, Fac Engn, Geotrop Ctr Trop Geoengn, Sch Civil Engn, Skudai 81310, Malaysia.

ENGINEERING WITH COMPUTERS, ; ():

Abstract

A proper planning schedule for tunnel boring machine (TBM) construction is considered as a necessary and difficult task in tunneling projects. Therefo......

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