Abstract
. In the coal-rock interface recognition (CIR) technology, signal process and recognition are the key parts. A method for CIR based on BP neural networks and fuzzy technique was proposed in this paper. By using the trail-and-error, the hidden layer dimension of the network was decided. Also the network training and weight modification were studied. In order to get a higher identification ratio, fuzzy neural networks (FNN) based data fusion was studied. For CIR, the structure and algorithm of FNN were determined. The results indicated that the test data can be used to train and simulate with the neural network and FNN. And the proposed method can be used in CIR with a higher recognition ratio.
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