Prediction of blast-induced vibration by adaptive neuro-fuzzy inference system in Karoun 3 power plant and dam

In this research a study was conducted to predict the ground vibrations produced by blasting projects in the structures of Karoun 3 power plant and dam (Izeh town, Iran) using a conventional statistical approach and a relatively new soft computing method known as the adaptive neuro-fuzzy inference system (ANFIS). For this aim a series of field measurements were planned and the required data were observed. A neuro-fuzzy model was constructed based on the data. In this model, the distance from the blasting site to the monitoring stations and the maximum charge weight per delay were selected as the input parameters of the constructed model, the output parameter being the peak particle velocity (PPV) as the vibration indicator. The results showed that the ANFIS model associated with the empirical model is a reliable and proper technique to predict the PPV caused from blasting.