摘要
该文针对瓦斯涌出量不容易确定的问题,提出基于改进T-S模糊神经网络的瓦斯涌出量预测方法,该方法很好的表达了瓦斯涌出量与其影响因素之间的复杂的非线性关系,解决了多输入单输出数据集的建模预测问题。预测结果与实际涌出量吻合度较高,表明了改进的T-S模糊神经网络在瓦斯涌出量预测上的可行性。为煤矿的安全生产中瓦斯涌出量的预测提供了一种新的途径。
For the problem of gas emission is not easy to determine, we proposed gas emission prediction new method based on improved T-S fuzzy neural network, the method expressed the complex nonlinear relationship between gas emission and its influencing factors perfectly, and solved the problem of modeling and forecasting for multi input and single output data sets. Prediction results had high degree of fit with actual gas emission, showed that the improved T-S fuzzy neural network in gas emission prediction was feasible.It provides a new method for prediction of gas emission in coal mine.
出处
《山东煤炭科技》
2015年第12期65-67,共3页
Shandong Coal Science and Technology
