通过工况的识别以及模型参数的离线辨识和在线优化，混合模型可以准确地模拟复杂过程在大范围内的动态特性。
By recognition of work condition, off-line identification and on-line optimization of parameters, hybrid model can be used to simulate dynamics of complex process correctly in a large scale.
载荷识别与系统参数辨识、动力特性修改等都属于振动的反问题。
Loading identification, like the system parameter identification and dynamic characteristics modification, is an inverse problem of structural vibration.
通过神经网络对一实际的油气藏系统进行建模和辨识，从而由新的神经网络模型可以获得参数识别结果。
After a practice oil or gas reservoir is modeled and identified by a neural network, the results of parameter identification are obtained by the new neural network model.
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