The present paper is focused on the prediction of oil and gas by means of neural network computing technique, and on the analysis of possible origins of pore_fluid pressure.
选用神经网络计算技术对松辽盆地深层孔隙流体压力进行了预测，并对孔隙流体压力的可能成因进行了分析。
The paper is to organically combine the time series analysis method and neural network technology in the fuzzy control technology and fractal theory to predict mine gas emission quantity.
将模糊控制技术、 分形理论中的时间序列分析方法与神经网络技术有机地结合起来，并运用于矿井瓦斯涌出量的预测中。
The error analysis and practical use show that combining relating analysis method with BP network method to predicting gas gushing quantity of mining faces is a feasible method.
通过误差分析及实际应用，证明将关联分析与BP网络结合起来开展采面瓦斯涌出量预测是一种可行的方法。
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