Artificial neural network for forecasting and classification of rockbursts

Abstract

A neural network model is developed for forecasting and classification of rockbursts by selection of some affecting factors as the inputted parameters, such as the geostress and compressive strength and tensile strength of rocks. With some engineering projects at home and aboard taken as learning and training samples, rockburst forecast is performed for an underground hydropower plant by use of the samples that have been trained stably. The results show that, compared with other forecasting methods, the artificial neural network model is objective and effective.