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Mine work face gas emission is the important basis for mine design, and has important practical significance for ventilation and safety production. Between mine gas emission and work face there are complex nonlinear relationships. The paper constructed a work face gas emission prediction model based on wavelet neural network. It based on statistics of a mine work face gas emission data, applied the...
Based on the theory of system engineering, coal mine production safety has been analyzed. From workers, production process, coal production and economy, coal mine production safety evaluation indexes have been confirmed, and then the BP neural network model of coal mine production safety evaluation has been built. After training and testing the model, the model can accurately evaluate the coal mine...
In this paper, the method of gray theory-BP Neural network was proposed and applied to predict the amount of gas gushing. It has established prediction model and realized the algorithm. And the proposed method has been compared with simple using the GM (1,1) model and simple using the BP neural network model to predict. The example shows that this method is relatively more accurate than simply using...
The gas supervision is a safety core of the coal mine production, which widespread existent a trouble, gas emergence big data, namely the pulse interference, the cause of the gas signal mistake alarm, is hardly resolved very often. In this paper, the reason and characteristics of gas emergence big data are analyzed to establish a kind of filter based on BP Neural Network. Through great quantities...
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