摘要
This article puts forward the gray markov prediction model to predict mine gas emission by combining grey system theory and markov chain theory. And GM (1, 1) model is established in the first place for grey data by the model. To eliminate the error, and improve the prediction accuracy of the model, secondary parameters fitting was done on the basis of GM (1, 1) model. And we get second parameter fitting for trend prediction. Then using Markov state transfer probability matrix prediction method to do quadratic fitting for its predictive value, which can improve the prediction precision of the volatile random variables. It proves the prediction results of the model are satisfactory by analyzing history data of gas emission prediction. This conclusion broadens the application scope of grey forecast model and provides a new method for mine gas emission scientific forecast.
This article puts forward the gray markov prediction model to predict mine gas emission by combining grey system theory and markov chain theory. And GM (1, 1) model is established in the first place for grey data by the model. To eliminate the error, and improve the prediction accuracy of the model, secondary parameters fitting was done on the basis of GM (1, 1) model. And we get second parameter fitting for trend prediction. Then using Markov state transfer probability matrix prediction method to do quadratic fitting for its predictive value, which can improve the prediction precision of the volatile random variables. It proves the prediction results of the model are satisfactory by analyzing history data of gas emission prediction. This conclusion broadens the application scope of grey forecast model and provides a new method for mine gas emission scientific forecast.
