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Coalmine gas concentration is a very complicated nonlinear dynamical system, which has obvious characteristics of chaos. Accurate prediction of coalmine gas concentration is very important to direct security production. However, data, got from in-wells, usually include noises, because of complex environment and multiple noises in-wells. Because of the capability of dividing frequency and diminishing...
Predicting water-irruption quantity from coal floor is of significance to coal mine safety production. It is complex nonlinear system related to influencing factors, Aimed at improving generalization, the predictive mode based on wavelet decomposition and artificial neural network was proposed, detailed learning algorithm was proposed and it was used in prediction. Both of the subsequent and the examination...
In view of the problems existing in the prediction methods of coal and gas outburst, a method for prediction of coal and gas outburst based on multi-agent information fusion is proposed. In the method, considering the measured data relevant to many influence factors, a multi-agent information fusion model for rapid, dynamic and accurate prediction of coal and gas outburst is given, Dempster-Shafer...
In order to realize safety prediction of workface stray current, it's important to confirm the characteristic indexes of workface stray current so as to insure the time margin and reliability of prediction. By analyzing the resistance distribution network of the system, the paper confirms the four parameters as follows to be the characteristic indexes of coalface stray current safety prediction: the...
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...
Presently, coal mine safety situation in China is still severe. One of the most important reasons is safety investment insufficient. Safety investment prediction can provide decision basis for efficient controlling and guiding safety investment. The paper analyzed coal mine safety investment influence factors and established coal mine safety investment prediction model based on support vector machine...
Based on introduction of the background and the limitations of present methods for coal and gas outburst, a hybrid method for prediction of coal and gas outburst based on soft sensor and data fusion combining many associated dynamic and static influence factors is proposed. In the method, the data fusion method based on arithmetic mean and batch estimation is used to process the dynamic influence...
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