煤与瓦斯突出灾害的预测枛——基于遗传和BP算法

Prediction of coal and gas outburst disasters based on genetic and BP algorithm

分析了煤与瓦斯突出的非线性动力系统特性和因素指标,利用神经网络的BP算法解决突出的主要性能指标和突出灾害等级的非线性网络连接.特别是利用遗传算法的全局优化能力, 对神经网络的连接权值、拓扑结构等进行进化操作,设计出具有较好性能参数和全局搜索能力的神经网络模型, 同时神经网络也可用于遗传算法的进化训练.遗传算法和神经网络的融合优化了煤与瓦斯突出灾害预测模型,并且该方法对其它灾害预测也有借鉴意义.

The article analyzes coal and gas ourbrusting unlinear dynamical system character and ingredient target ,using BP algorithms of NN solves main capability target and disaster grade unlinearity network connections of outbrust is carried out .Especially using entire optimization ability of genetic Algorithms, anagenesis operation on connection right value of NN model, topologv structure and so on .And NN model is built with preferable capability parameter and entire search ability. At the same time, NN can be used in Back Propagation抯 anagenesis training. Inosculate of Genetic Algorithms and NN not only optimizes prediction model about mine and gas ,but also is used for reference in other disaster forecasts.