摘要
瓦斯灾害是煤矿中最严重的灾害之一,瓦斯治理是我国煤矿安全的主攻方向。瓦斯涌出量的预测对遏制矿山瓦斯灾害、保证矿山安全和矿山技术经济指标都有重要意义。传统的方法预测精度不高,而神经网络在构建网络模型时具有一定的主观性。将混沌时间序列理论引入瓦斯预测中,为构建神经网络模型提供理论依据。通过实例证明在实际应用中是可行的。
Gas explosion is one of the serious calamities in the coal mine. Governing the gas is crucial in guaranteeing the safety of the coal mine in our country. The anticipation of the quantity of gushing gas means much to the inhibition of gas combustion in the coal mine, maintaining the safety arid the index of technology and economic in the coal mine. The traditional method is not accurate enough and the neural net is subjective once it is used to construct circuital models. With the introducing the theory of muddleheaded time series into the anticipation of gas, the theoretical basic is provided to construct the neural circuital model. This method is improved to be helpful by examples.
出处
《煤》
2005年第5期7-9,11,共4页
Coal
关键词
瓦斯涌出量
混沌时间序列
神经网络
预测
quantity of gushing gas
chaos time sequence
neural net
anticipation
作者简介
黄炜伟（1982-）,男,山西长治人,2003年毕业于中国矿业大学,从事生产技术工作.
