CAJ | 학술논문

影响煤与瓦斯突出的各种要素与突出现象之间的关系复杂,且具有明显的非线性特点.BP人工神经网络模型可以很好地逼近这种非线性函数关系.基于煤与瓦斯突出特征指标的分析,建立了合理的单隐层结构的BP预测模型,并利用MATLAB神经网络工具箱实现了模型的训练与预测,应用结果表明,这种突出预测方法具有很高的计算效率和预测精度.
영향매여와사돌출적각충요소여돌출현상지간적관계복잡,차구유명현적비선성특점.BP인공신경망락모형가이흔호지핍근저충비선성함수관계.기우매여와사돌출특정지표적분석,건립료합리적단은층결구적BP예측모형,병이용MATLAB신경망락공구상실현료모형적훈련여예측,응용결과표명,저충돌출예측방법구유흔고적계산효솔화예측정도.
It is very complex between the each kind of essential factor of the coal and gas prominent and the phenomenon of the prominent,and there is very obvious misalignment character.The BP artificial neural networks model,we can approach this kind of nonlinear function relations well.Based on the analysis of the coal and the gas prominent character index,we can establish the reasonable single cryptoclastic texture BP forecast medal,and realize the training and the forecast to the model which using the MATLAB neural network toolbox.The application result indicated that this prominent forecast technique has the very high counting yield and the forecast precision.