FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4286512654> ?p ?o ?g. }

• W4286512654 endingPage "100819" @default.
• W4286512654 startingPage "100819" @default.
• W4286512654 abstract "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 Optimizer (ALO), Loin swarm optimization (LSO) and Seagull optimization algorithm (SOA)) and the Extreme learning machine (ELM) model, namely ELM-ALO, ELM-LSO and ELM-SOA model respectively. The dataset consists of 1, 286 samples from the Pahang Selangor Raw Water Transfer (PSRWT) tunnel project in Malaysia, and containing six parameters (rock quality designation (RQD), uniaxial compressive strength (UCS), rock mass rating (RMR), Brazilian tensile strength (BTS), thrust force per cutter (TFC) and revolution per minutes (RPM)) from rock mass and machines. In order to evaluate the prediction performance of different hybrid models, the root mean square error (RMSE), the mean absolute error (MAE), the mean square error (MSE), the determination coefficient (R2), the sum of square error (SSE), and the variance accounted for (VAF) were adopted as the performance indicators. The results show that ELM-LSO is the best model to predict AR. Sensitivity analysis shows the importance of all considerations to AR. TFC, RPM and RMR are the three most important parameters. But this is not absolute, more parameters need to be taken into account in AR prediction. Meanwhile, the ELM-LSO model proposed in this paper can be used as a new method to predict AR." @default.
• W4286512654 created "2022-07-22" @default.
• W4286512654 creator A5001490863 @default.
• W4286512654 creator A5011370924 @default.
• W4286512654 creator A5017858590 @default.
• W4286512654 creator A5024434626 @default.
• W4286512654 creator A5041698589 @default.
• W4286512654 creator A5043064343 @default.
• W4286512654 creator A5073485469 @default.
• W4286512654 date "2022-09-01" @default.
• W4286512654 modified "2023-10-12" @default.
• W4286512654 title "Developing hybrid ELM-ALO, ELM-LSO and ELM-SOA models for predicting advance rate of TBM" @default.
• W4286512654 cites W1966197180 @default.
• W4286512654 cites W1980490383 @default.
• W4286512654 cites W2001979953 @default.
• W4286512654 cites W2012218190 @default.
• W4286512654 cites W2024921522 @default.
• W4286512654 cites W2054224043 @default.
• W4286512654 cites W2061438946 @default.
• W4286512654 cites W2071455833 @default.
• W4286512654 cites W2091346452 @default.
• W4286512654 cites W2093953062 @default.
• W4286512654 cites W2094012998 @default.
• W4286512654 cites W2110529327 @default.
• W4286512654 cites W2111072639 @default.
• W4286512654 cites W2137296881 @default.
• W4286512654 cites W2163592787 @default.
• W4286512654 cites W2166186246 @default.
• W4286512654 cites W2167538629 @default.
• W4286512654 cites W2290883490 @default.
• W4286512654 cites W2416069211 @default.
• W4286512654 cites W2566958870 @default.
• W4286512654 cites W2585392941 @default.
• W4286512654 cites W2604737493 @default.
• W4286512654 cites W2648578256 @default.
• W4286512654 cites W2758887415 @default.
• W4286512654 cites W2768643127 @default.
• W4286512654 cites W2778951166 @default.
• W4286512654 cites W2794172892 @default.
• W4286512654 cites W2802744659 @default.
• W4286512654 cites W2809438835 @default.
• W4286512654 cites W2885889990 @default.
• W4286512654 cites W2902421512 @default.
• W4286512654 cites W2920965395 @default.
• W4286512654 cites W2942549247 @default.
• W4286512654 cites W2946640301 @default.
• W4286512654 cites W2970896257 @default.
• W4286512654 cites W2993501443 @default.
• W4286512654 cites W2998566163 @default.
• W4286512654 cites W3009921884 @default.
• W4286512654 cites W3013477797 @default.
• W4286512654 cites W3023424901 @default.
• W4286512654 cites W3035846893 @default.
• W4286512654 cites W3036700357 @default.
• W4286512654 cites W3041981321 @default.
• W4286512654 cites W3087374167 @default.
• W4286512654 cites W3095300548 @default.
• W4286512654 cites W3097465463 @default.
• W4286512654 cites W3133107848 @default.
• W4286512654 cites W3185288064 @default.
• W4286512654 cites W3201203558 @default.
• W4286512654 cites W3205140864 @default.
• W4286512654 cites W3210258470 @default.
• W4286512654 cites W4206095525 @default.
• W4286512654 cites W4206258478 @default.
• W4286512654 cites W4210581009 @default.
• W4286512654 cites W4225666890 @default.
• W4286512654 cites W4281629107 @default.
• W4286512654 cites W4286324596 @default.
• W4286512654 doi "https://doi.org/10.1016/j.trgeo.2022.100819" @default.
• W4286512654 hasPublicationYear "2022" @default.
• W4286512654 type Work @default.
• W4286512654 citedByCount "27" @default.
• W4286512654 countsByYear W42865126542022 @default.
• W4286512654 countsByYear W42865126542023 @default.
• W4286512654 crossrefType "journal-article" @default.
• W4286512654 hasAuthorship W4286512654A5001490863 @default.
• W4286512654 hasAuthorship W4286512654A5011370924 @default.
• W4286512654 hasAuthorship W4286512654A5017858590 @default.
• W4286512654 hasAuthorship W4286512654A5024434626 @default.
• W4286512654 hasAuthorship W4286512654A5041698589 @default.
• W4286512654 hasAuthorship W4286512654A5043064343 @default.
• W4286512654 hasAuthorship W4286512654A5073485469 @default.
• W4286512654 hasConcept C105795698 @default.
• W4286512654 hasConcept C11413529 @default.
• W4286512654 hasConcept C119857082 @default.
• W4286512654 hasConcept C127413603 @default.
• W4286512654 hasConcept C128990827 @default.
• W4286512654 hasConcept C139945424 @default.
• W4286512654 hasConcept C21200559 @default.
• W4286512654 hasConcept C24326235 @default.
• W4286512654 hasConcept C2780150128 @default.
• W4286512654 hasConcept C33923547 @default.
• W4286512654 hasConcept C41008148 @default.
• W4286512654 hasConcept C50644808 @default.
• W4286512654 hasConceptScore W4286512654C105795698 @default.
• W4286512654 hasConceptScore W4286512654C11413529 @default.
• W4286512654 hasConceptScore W4286512654C119857082 @default.

• next