基于贝叶斯正则化BP人工神经网络的煤与瓦斯突出预测的研究

文章介绍了BP人工神经网络和贝叶斯正则化算法的原理,探讨了贝叶斯正则化BP人工神经网络模型的建立,通过改变隐含层神经元个数的实验建立了只含1个隐含层且隐含层仅需1个神经元的煤与瓦斯突出预测模型的最佳网络结构。对该网络采用煤与瓦斯突出的预测指标进行训练、检测的结果表明,该网络预测的煤与瓦斯突出的危险程度与实际情况完全吻合;对该网络输入层输入的煤与瓦斯突出的预测指标、对输出层输出的预测结果的权值进行分析的结果表明,煤层地质构造类型对煤与瓦斯突出的影响为最大。上述研究结果对煤与瓦斯突出的预测预防研究、提高煤与瓦斯突出预测的准确性具有一定的参考价值。

Research of Prediction of Coal and Gas Outburst Based on BP Artificial Neural Network Utilizing Bayesian Regularization

The paper introduced principle of BP artificial neural network and Bayesian regularization(algorithm,) discussed establishment of model of BP artificial neural network utilizing Bayesian regularization,established the best network structure of prediction model of coal and gas outburst which had only one hidden layer with only one neural node through experiment of changing quantity of neural node in(hidden) layer of the network.The result of using prediction indexes of coal and gas outburst to train and chec...