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Predicting potential of controlled blasting-induced liquefaction using neural networks and neuro -fuzzy system
2017
Scientia Iranica. International Journal of Science and Technology
In recent years, controlled blasting has turned into an e cient method for evaluation of soil liquefaction on a real scale and of ground improvement techniques. Predicting blast-induced soil liquefaction using collected information can be an e ective step in the study of blast-induced liquefaction. In this study, to estimate residual pore pressure ratio, rst, a multi-layer perceptron neural network is used in which error (RMS) for the network was calculated as 0.105. Next, a neuro-fuzzy
doi:10.24200/sci.2017.4184
fatcat:mqv3ilzlabeq3gubr2irkbgrcu