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A MSH(Mine Subsidence Hazard) index has been developed to estimate the subsidence possibility of an abandoned mine by means of an artificial neural network (ANN) and an interaction matrix. For this, 19 influence factors of mine subsidence were determined through a literature study, and the influence factors for 287 subsidence points at 38 abandoned mines were selected first, of which 108 points (34 abandoned mines) having high data quality were used for learning of ANN. Each influence factor of which range is widely distributed was classified into seven ranges to use it as a learning data of ANN. Interaction matrixes were constructed by an ANN analysis, and a MSH index for each subsidence point was calculated from influence factors as well as influence weights that are from the interaction matrix. The result shows that MSH index ranges between 37 and 66. The average of MSH index for Non-coal mines is 54, which is 13% higher than the one for coal mines of which average MSH index is 47.

The Development of Subsidence Hazard Index for an Abandoned Mine Using Artificial Neural Network and Interaction Matrix