Abstract
Tunnel Boring Machine (TBM) penetration rate prediction is one of the most important problem in tunneling projects. Estimating of Tunnel Boring Machine (TBM) penetration rate can considerably reduce the costs of tunneling projects. In this study, Datasets including Uniaxial Compressive Strength, Brazilian Tensile Strength, Density and Joint Angle as input parameters and Rate of Penetration as an output parameter. The aim of this study is estimating the penetration rate of tunnel boring machines using fuzzy logic method, Harmony search algorithm (HSA) and Particle Swarm Optimization (PSO) in the Nosoud water conveyance Tunnel. The modeling results showed that the fuzzy model has a significant advantage over the PSO and HSA.
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Afradi, A., Ebrahimabadi, A. & Hallajian, T. Prediction of TBM Penetration Rate Using Fuzzy Logic, Particle Swarm Optimization and Harmony Search Algorithm. Geotech Geol Eng 40, 1513–1536 (2022). https://doi.org/10.1007/s10706-021-01982-x
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DOI: https://doi.org/10.1007/s10706-021-01982-x