A Review of Artificial Intelligent for Prediction Ground Vibration in Blasting - Risaldi Hidayat; Tedy Agung Cahyadi; Eddy Winarno; Singgih Saptono; S. Koesnaryo (Retii, 2020)
Blasting activities cause ground vibrations that affect the potential for ground displacement in surface mining. That will have an impact on the stability of the slope and environmental problems. Therefore, it is necessary to analyze the prediction ground vibrations measured by peak particle velocity (PPV). Artificial Intelligent (AI) has an important role to overcome the limitations of parameters used, uncertainty, and inaccuracy than conventional methods. AI for prediction ground vibration has grown a lot in recent years. To find out an accurate and effective AI technique, the authors compare several techniques by evaluating their strengths and weaknesses based on literature studies. The ICA-M5Rules model and ICA-ANN model are techniques that have high accuracy and flexibility of use than other presented techniques. And related to the use of parameters, there are other parameters that play an important role which will be reviewed in this journal.