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Prediction of TBM Penetration Rate Using Fuzzy Logic, Particle Swarm Optimization and Harmony Search Algorithm
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Prediction of TBM Penetration Rate Using Fuzzy Logic, Particle Swarm Optimization and Harmony Search Algorithm
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Journal Article
Prediction of TBM Penetration Rate Using Fuzzy Logic, Particle Swarm Optimization and Harmony Search Algorithm
2022
Overview
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.
Publisher
Springer International Publishing,Springer Nature B.V
