A vibration predicting method by artificial nerve network model is suggested on the basis of analysis on current vibration predicting method.
文章提出了应用人工神经网络模型进行颤振预报的方法。
Based on the measured vibration data, it found out the characteristic values that will reflect the vibrating condition and suggested a way to establish the artificial nerve network model.
结合实测振动数据，找出了足以反映振动状态变化的特征量，并给出了人工神经网络模型的程序实现方法。
The paper introduces the keystone of the artificial nerve network and the usual forward feedback network model. And the model theory was applied in the reservoir optimum operation.
本文介绍了人工神经网络基本原理和常用的前馈式网络模型，并将该模型理论应用到水库优化调度之中。
This paper has introduced briefly the principle and method of BP model of the artificial nerve cell network, and discussed its application experience on the meteorological forecast.
结合气象应用简要介绍人工神经元网络BP模型的原理和方法，对其在气象预测中的应用经验作了评述。
Comparing with the traditional valve method, the artificial nerve network has advantages that setting up model fast, realization method simple and solution speed quick and so on.
相对于传统的数值方法，人工神经网络具有建模迅速、实现方法简单、求解速度快等优点。
By means of BP (error back propagation) artificial nerve network, with data from alarm, weather and engineering documents, microwave hop performance analysis and forecast model is established.
利用神经网络的误差反向传播算法(BP算法)，结合告警、天气和工程设计几方面的数据资料建立了微波中继段告警分析预测模型。
By means of BP (error back propagation) artificial nerve network, with data from alarm, weather and engineering documents, microwave hop performance analysis and forecast model is established.
利用神经网络的误差反向传播算法(BP算法)，结合告警、天气和工程设计几方面的数据资料建立了微波中继段告警分析预测模型。
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