Abstract
This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for the evaluation of ground vibration due to blasting. The training of ANFIS was performed by a hybrid method of gradient descent method and least square algorithm. The least square algorithm is used to optimize the consequent parameters with the premise parameters fixed. Seven factors including the hole depth, burden, spacing, stemming, maximum charge per delay, charge and distance, were taken into account as the input parameters of the ANFIS model, whereas the peak particle velocity is the output parameter. The results show that the proposed ANFIS model is a feasible, efficient, and accurate tool for predicting the ground vibration due to blasting.
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Xue, X., Yang, X. & Li, P. Evaluation of Ground Vibration Due to Blasting Using Fuzzy Logic. Geotech Geol Eng 35, 1231–1237 (2017). https://doi.org/10.1007/s10706-017-0162-7
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DOI: https://doi.org/10.1007/s10706-017-0162-7