Optimized neural network using beetle antennae search for predicting the unconfined compressive strength of jet grouting coalcretes

Summary This investigation studied the coalcrete, a new supporting material produced by jet grouting (JG) for supporting surrounding coal seams. For support design, the unconfined compressive strength (UCS) of the coalcrete is an essential parameter to evaluate the jet grouting effect in coal mines....

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Vydané v:	International journal for numerical and analytical methods in geomechanics Ročník 43; číslo 4; s. 801 - 813
Hlavní autori:	Sun, Yuantian, Zhang, Junfei, Li, Guichen, Wang, Yuhang, Sun, Junbo, Jiang, Chao
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Bognor Regis Wiley Subscription Services, Inc 01.03.2019
Predmet:	Antennae Architecture Artificial neural networks Back propagation networks back propagation neural network beetle antennae search algorithm Cement Coal Coal mines Compressive strength Concrete Curing Curing (processing) Grout Grouting Jet grouting jet grouting coalcrete Mathematical models Modelling Neural networks prediction Predictions Regression analysis Sensitivity analysis Support vector machines unconfined compressive strength Water-cement ratio
ISSN:	0363-9061, 1096-9853
On-line prístup:	Získať plný text
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