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 system consists of graphic user's interface module, sample processing module, neural network structural module and neural network computing module.
该系统主要由以下模块构成：用户界面模块、网络模型模块、样本处理模块、神经网络计算模块以及神经网络训练结果显示模块。
The application shows that the algorithms simplify the computing complexity of process neural networks, and raise the efficiency of the network learning and the adaptability to real problem resolving.
应用表明，算法简化了过程神经网络的计算复杂度，提高了网络学习效率和对实际问题求解的适应性。
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