On the application of catastrophe progression method to predicting the likely mining collapse accidents

This paper intends to present an integrated evaluation method proposed by us to predict the likely mining collapse accidents based on the catastrophe progression theory. In our study,we have explored a lot of multi-layer objective decomposition activities in the mine,which can be divided into seven influential factors according to the stability of mining geological structures,including volume fractions of mining collapse,vertical depth of the mining layers,their geological structure,coal seam-angular slanting,overload thickness,the overload patterns and some other factors involved. In addition,a series of other basically involved thoughts and approaches to the catastrophe progression theory have also been introduced. Besides,we have also explored and worked out an index system of factors for better identification and determination of the degree of importance of the chief factors which may contribute to the mining collapse accidents. Then,we have conducted a recursive calculation in accordance with the normalization formula and the fuzzy factors' influence which may be produced by combining the catastrophe theory and fuzzy math theory in hoping to obtain the catastrophic affiliated functional values. And,last of all,the investigation and testing results with the catastrophic affiliated functional values of the samples have been deduced to predict such collapse accidents along with a few data gained from the actual engineering projects selected to test the experimental data. In comparison,with the article neural network (ANN) method,the results prove that the catastrophe progression method is perfect in performance,high in forecasting probability,which prove it both highly effective in evaluation as well as academically valuable.