关键词: 混合pi-sigma模糊神经网络, 瓦斯涌出量, 预测, 图形用户界面

Abstract: A gas emission prediction model established by using reasoning method of hybrid pi-sigma fuzzy neural networks was proposed. The model adopted Gaussian function as a fuzzy membership function, and the membership functions and conclusions parameters of the model could be adjusted online dynamically. Compared with the neural network prediction model, the method has characteristics of clear physical meaning, clear principle, fast convergence, high prediction accuracy and so on. The gas emission data of a coal mine simulation results show that the prediction has a high accuracy, fast convergence and the prediction results can be repeated, it is proved that the method is effective. In order to facilitate the practical application, the authors developed a Graphical User Interface (GUI) application interface in the Matlab environment, and gave the method and prediction results. The experiments also show that, for the data, the generalization ability of the model is best when the training accuracy is set 0.001, and the training accuracy and the prediction accuracy of the model do not have positive relationship.

Key words: hybrid pi-sigma neural fuzzy network, gas emission, prediction, Graphical User Interface （GUI）