摘要
针对煤与瓦斯突出的准确预测与控制,提出了一种基于最大最小蚂蚁系统与BP神经网络相结合的煤与瓦斯突出预测方法,将最大最小蚂蚁系统的全局优化与BP神经网络算法的自适应求解相结合,以煤与瓦斯突出影响因素作为输入量,并寻找最优初始解,减少了在煤与瓦斯预测过程中收敛时间。实验结果表明,该检测方法具有较高的准确性和可行性。
Focused on accurate prediction and control of coal gas outburst , it provides a new prediction method of coal gas outburst based on MMAS and BP neural network .It combined the o-verall optimizing of MMAS and self -adaptively solving of BP neural network together;make the in-fluencing factors of coal gas outburst as input value , seeking for most optimized original solution .It reduces the convergence time in prediction and the experiment showed that this method is of higher accuracy and it is feasible .
出处
《电气防爆》
2014年第2期4-7,共4页
Electric Explosion Protection
关键词
瓦斯突出
最大最小蚂蚁系统
BP神经网络
coal gas outburst max-min ant system （ MMAS） BP （ Back Propagation ） neu-ral network
