Journal
APPLIED ACOUSTICS
Volume 152, Issue -, Pages 73-78Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.apacoust.2019.03.023
Keywords
Peak particle velocity; Adaptive neuro-fuzzy inference system; Blasting; Ground vibration
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In this study, subtractive clustering algorithm (SCA) and fuzzy c-mean clustering (FCM) method were employed to construct an adaptive neuro-fuzzy inference system (ANFIS) model for the prediction of blast-induced ground vibration. To develop the ANFIS models, the charge weight per delay, distance, and scaled distance were taken into account as the input parameters, while peak particle velocity (PPV) was the output parameter. The performances of the both two ANFIS models and some conventional methods were compared in terms of three statistical indexes. The results shown that the FCM-ANFIS model can provide a precise evaluation of PPV if proper input data are provided. (C) 2019 Elsevier Ltd. All rights reserved.
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