基于免疫遗传算法的煤与瓦斯突出预测研究  

Coal and Gas Outburst Forecasting Based on Immune Genetic Algorithm

作　　者：朱玉[1] 张虹[1] 苏成[1] 

机构地区：[1]中国矿业大学环境与测绘学院,江苏徐州221116

出　　处：《中国矿业大学学报》2009年第1期125-130,共6页Journal of China University of Mining & Technology

基　　金：江苏省自然科学基金项目(BK2005021);江苏省普通高校研究生科研创新计划项目(CXB-1392)

摘　　要：根据影响煤与瓦斯突出的各个因素与突出强度之间存在的复杂的非线性映射关系,建立了突出强度预测的BP网络模型.针对BP网络收敛速度慢和易陷入局部极小值及基于遗传算法的BP网络易出现未成熟收敛问题,提出了一种基于免疫遗传算法(IGA)的BP网络,即利用IGA实现对BP网络的优化.IGA在遗传算法(GA)的基础上引入生物免疫系统中的多样性保持机制和抗体浓度调节机制,有效地克服了GA算法的搜索效率低、个体多样性差及早熟现象,提高了算法的收敛性能.结果表明:将基于IGA的BP网络应用于煤与瓦斯突出强度预测,该算法设计的BP网络具有较快的收敛速度和较强的全局收敛性能,在煤与瓦斯突出预测中取得了良好效果.There are a lot of factors that affect the intensity of coal and gas outburst, and among those there is a complicated and nonlinear relationship, so a BP neural network model for forecasting the intensity was constructed. Aimed at the shortcoming of the traditional BP neural network, such as slow training speed, easy to be trapped into local optimums, and the premature convergence of Genetic Algorithm（GA） BP neural network, a method to design the BP neural network based on Immune Genetic Algorithm（IGA）was proposed. The mechanisms of diversity maintaining and antibody density regulation exhibited in a biological immune system were introduced into IGA based on genetic algorithm. The proposed algorithm overcame the problems of GA on search efficiency,individual diversity and premature,and enhanced the convergent performance effectively. The results show that the BP neural network designed by IGA has better performance on convergent speed and global convergence, and the prediction precision is improved, which illustrates IGA-BP neural network has certain value on coal and gas outburst prediction.

关 键 词：免疫遗传算法(IGA) BP网络 煤与瓦斯突出 预测 

分 类 号：TD713[矿业工程—矿井通风与安全]