Rough set and neural network based risk evaluation under coalmine with detect mobile robot

Abstract

The objective of this paper is to present a novel method based on detect mobile robot for risk evaluation under coal mine, the approach is based on rough set and neural network theories, the data of the evaluation chart were reduced by using rough sets reduction function and then the reduced data were transferred to the BP neural network as training data. This method provides a new concept for the establishment of environmental safety assessment models. The result of the experiments shows that this method is valid for the assessment of the gas safety and the estimated result is very reliable.