This paper investigates the identification of unknown nonlinear dynamical system using multilayered feedforward neural network with a single hidden layer.
本文探讨了只用单个隐含层的前向神经网络对未知非线性动态系统的识别。
Based on artificial neural network theory, using routine logging data in fracture identification is studied.
本文基于人工神经网络理论，开展了常规测井资料识别评价裂缝的研究。
After noise reduction in the signal, using "wavelet packet-energy" to extract the characteristic vector and input them to the neural network for fault identification.
在对采集到的信号降噪后，利用“小波包-能量”法提取特征量，并将其输入到神经网络中进行故障识别。
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