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传统的冯·诺依曼程序存储式计算机擅长于数据处理，但是在类似于面貌及声音识别这样一些简单的认知问题方面，与人类相差很大．这种差异推动了神经网络的研究．本文讨论了误差反向传播网络（ＢＰ）．给出了ＢＰ网络在储层横向预测测方面的应用．
The traditional von Neumann program-storage computer is good at data processing, but differs from humans in simple cognitive issues like face recognition and voice recognition. This difference drives the study of neural networks. This article discusses the error backpropagation network (BP). The application of BP network in reservoir lateral prediction is given.