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 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.
基于表层语义理解的工作，我们继续进行深层语义计算的研究，真正意义上的实现语义神经网络的自然语言理解。
On the basis of this work, we continue to carry on the research of Deep-seated Semantic Computing and really realize the understanding of the nature language with the Semantic Neural Network.
对现行的深层搅拌桩设计方法存在的问题进行探讨，提出了用人工神经网络模型对复合地基承载力进行计算的新思路。
A new athematics model of artificialneural network is set up and applied to the calculation of the bearing capacity of compound foundation to deep mixing pile.
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