基于灰色GM(1,1)新陈代谢模型的矿井瓦斯涌出量动态预测

Predicting the gas emission of the mine based on the gray GM (1, 1) metabolism model Dynamic prediction model of gas emission based on Grey GM (1, 1) metabolism model

矿井工作面瓦斯涌出是一个动态不确定的过程,因此最新瓦斯涌出数据的研究至关重要,本文将灰色GM(1,1)模型瓦斯涌出量预测结果加入原始数列,对原始数据序列的信息进行更新,建立了矿井瓦斯涌出量GM(1,1)新陈代谢动态预测模型,采用残差检验法对该模型精度进行检验,其平均相对误差为3.861%,预测精度明显优于GM(1,1)模型,提高了灰色GM(1,1)模型预测瓦斯涌出量的精度。

In order to improve the accuracy of the gray GM （1,1） model for predicting the coalface gas emission, by the way of adding the new prediction data from the gray GM （1,1） model, and remove the old data, the gray GM （1,1） metabolism model for predicting the gas emission is established in the paper. Tested by residual analysis, the average relative error of the model gray GM （1,1） metabolism model is 3.861%, meet the accuracy requirement of the gray theory model. At the same time, compared with the grey GM （1, 1） model, the prediction results show that the average relative error of the GM （1,1） metabolism model is lower, and the precision accuracy of the GM （1,1） metabolism model is ob- viously superior to the gray GM （l,1） model.