Methodology and application on size-limited structure predictions with ANN based on loop overlapping theory:a case study of Lingzi Coal Mine in Zibo
WU Qiang
CHEN Hong
LIU Shou-qiang
Abstract：Based on loop overlapping theory and the artificial neural networks (ANN), a set of complete theory system and work method were put forward to forecast the size-limited structure. Took the Lingzi Coal Mine in Zibo for example,the four master factors,that is the coal seam dip angle, thickness, the gas accumulation quantity and the gushing water volume change,were selected. These factors control the size-limited structures of the front working face in Lingzi Coal Mine. Then,the nonlinearity model was established to predict the size-limited structures in the front coal mine working face in the first well. The field test result indicates that if the massive information of the master factors can be mastered in coal exploitation,the distributing feature of the size-limited structure can be predicted accurately in the front of face mining. The technique of ANN based on loop overlapping theory solves the difficult problem in predicting the size-limited structure which induces to great mine accident.
Keywords：loop overlapping theoryartificial neural network (ANN)prediction for size-limited structuresworking face
Publication Date：2010-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 449-453 )